Inverse synthetic aperture radar (ISAR) is an important tool for non-cooperative ship imaging, and one key step of ISAR imaging is range alignment. To achieve the range alignment with high precision, efficiency and robustness, an improved ISAR range alignment method based on maximum contrast is proposed in this paper, which takes the maximum contrast of average range profile as the optimisation criterion to perform the range alignment. Compared with the minimum entropy method, this method is with lower computation complexity and faster convergence rate. Thus the method proposed in this article is more effective and more robust. Computer simulation and real data experiment validate the effectiveness and robustness of the proposed method.

Aiming at the problem that azimuth cosinusoidal phase-modulation cannot be directly implemented in application, and two-dimensional modulation can only be carried out in azimuth and distance, respectively, a joint azimuth-range jamming method based on time delay for ISAR is proposed. The ISAR signal captured by jammer is delayed in the fast time domain. The ISAR signal captured by jammer is then delayed in the fast time domain to achieve the cosinusoidal phase-modulation because the time delay is a function of slow time. The blind frequency shift modulation term is introduced at the same time. The simulation results show that the target will be completely submerged in the multiple jamming strips formed by the jamming signal, and the feasibility and effectiveness of the method are verified.

In the actual scenario, the target is often located in a certain environment and the influence of the environment scattering and the scattering from the multipath interactions between the target and background environment can make the synthetic aperture radar (SAR) characteristics quite different from those of the targets in the free space. The SAR imaging of the low-altitude target in the complex environment is not well studied yet. This study has developed an electromagnetic scattering model to illustrate the SAR characteristics of a low-flying airplane target at the maritime scene. The results can reflect the influence of sea surface scattering and the multipath scattering effect very clear. The results can also help understanding the SAR characteristics of the low-flying target at the practical maritime scene.

Conventional 3-dimensional (3D) space-time adaptive processing (STAP) has achieved good performance for non-stationary clutter suppression. However, the performance of 3D STAP rapidly degrades when applied to heterogeneous clutter environment due to the requirement of a large number of independent and identically distributed training samples to estimate the clutter covariance matrix. This study applies an efficient sparse recovery algorithm, i.e. multiple sparse Bayesian learning (MSBL), with tuning, to solve the limited sample problem of 3D STAP in airborne radar. Differing with the conventional 2D sparsity-based STAP, the proposed method utilises the sparsity of clutter in elevation-azimuth-Doppler domain and recovers the 3D clutter spectrum. Whereas in its’ large computational load, a fast algorithm extending the relevance vector machine is also considered.

Low observable moving target-detection technology under clutter background is the key factor affecting the radar performance. Here, frequency diverse array (FDA) MIMO radar is investigated for low-observable moving target detection. FDA-MIMO radar not only has all the advantages of phased array and MIMO radar, but also can make a two-dimensional joint estimation of the target distance and azimuth. In order to achieve coherent integration for Doppler processing, a novel three-dimensional processing method is proposed, i.e. space-range-Doppler focus (SRDF) processing. It utilises the property of FDA and high-resolution Doppler processing of MIMO. After discussing signal model of FDA-MIMO radar, the flowchart of SRDF-based low-observable moving target detection and estimation is provided. Finally, simulation of moving target detection in clutter background verifies that proposed method has better ability for joint angle-range-Doppler processing with higher resolutions.

Unimodular (i.e. constant modulus) sequences with good correlation properties are useful in many areas like communication and radar/sonar. However, several algorithms for designing unimodular sequences with the minimisation of correlation sidelobes, which usually cost a lot of calculation time and hardware resources, are not suitable for real-time applications. Here, a fast algorithm, the inversion of the shaped output with a mismatched filter (ISO-MMF), is proposed to suppress correlation sidelobes to the designed level over specified regions. The closed-form solution is presented to give a fast implementation without thousands of iterations. Several experiments are also conducted to illustrate the effectiveness and efficiency of the proposed method. The theoretical evaluation and experiments show that the proposed ISO-MMF significantly improves the effectiveness of minimising correlation sidelobes and yields better results than existing methods.

An improved features from accelerated segment test (FAST) corner-detection method for suppressing SAR image speckle noise is proposed here. The direction of the corner candidate is first computed by the law of universal gravitation and is introduced into corner detection to divide the 16 pixels around the corner candidate into two groups without repeatedly searching. Then, the similarity between the corner candidate and its surrounding pixels is computed to suppress the points affected by SAR speckle noise. Finally, the phenomenon of corner density is eliminated based on non-maximum suppression. The experimental results show that authors’ method has better suppressing effect compared with FAST-8 and SIFT corner-detection methods.

The compressed sensing (CS) radar receiver based on the theory of CS has a great advantage in receiving wide-band signal and can receive high-frequency radar signal at a sampling rate far lower than the traditional receiver. However, in order to obtain the information of the target signal, the parameters of the reconstructed signal still need to be measured by conventional methods. In order to make full use of the compressed sampling and the characteristics of radar signals, this study proposed a cascading dictionary matching pursuit algorithm based on block-sparsity (BS-CDMP) to achieve fast identification and reconstruction of received signals. First, a signal-level redundant dictionary is constructed for quickly identifying the signal in which the authors are interested in. Then, they study the feasibility of cascading the signal-level redundant dictionary and the DFT basis as a whole sparsity dictionary. Finally, the block sparsity is introduced for the selection of different parts of the dictionary during greedy iteration. Experimental results show that their proposed algorithm has considerable and universal reconfiguration performance and can directly perform fast reconstruction and recognition of the target signal.

This study addresses the target localisation problem using bistatic range (BR) measurements in a multi-base system based on external emitter radar. An asymptotically efficient Taylor series method is proposed for target localisation. The initial value for Taylor series method is provided by some algebraic closed-form positioning algorithms, rather than priori initial guesses. The localisation convergence problem can also be avoided unless in an extremely large measurement noise. The proposed method can be applied to both critically determined and over-determined conditions. The performance is verified and evaluated through simulations. The results show that the method can realise Cramer-Rao lower bound (CRLB) precision under Gaussian measurement noise. In addition, the method is superior to the existing localisation estimation in positioning accuracy and robustness.

In the past few decades, many manoeuvring target-tracking methods have been proposed. However, most of these methods require some priori knowledge about the target, which is hard to obtain in many scenarios. Here, a priori-knowledge-free (PKF) manoeuvring target-tracking method is proposed by introducing a time-varying polynomial-function-based motion model. The model order and coefficients are real-time estimated to guarantee a steady performance in both manoeuvring and non-manoeuvring situations. Numerical results are provided to validate the effectiveness of the proposed method.

To improve the detection performance in the presence of target-steering vector mismatches, a novel robust adaptive matched filter (AMF) detector for compound Gaussian clutter is proposed. First, the multivariate inverse Gaussian distribution is first introduced to compound Gaussian clutter model. Second, the texture value is estimated with maximum a posteriori (MAP) estimator in spatial domain, which has a closed form and is not affected by the target's steering vector mismatch. A robust AMF detector is derived based on this estimation. Simulation results demonstrate that the proposed detector can achieve better performance in the presence of target-steering vector mismatches.

Recently, correlation filter-based trackers have received extensive researching interest because of their simplicity and superior running speed. However, such trackers perform poorly when the target undergoes occlusion, viewpoint change, or other challenging attributes due to pre-defined sampling strategy. To tackle these issues, the authors propose an adaptive region proposal strategy to facilitate object tracking. To be more specific, a novel tracking monitoring indicator is advocated to forecast tracking failure. Afterwards, detection and scale proposals were incorporated, respectively, to recover from model drift as well as handle aspect ratio variation. The algorithm was tested on several challenging video sequences, which demonstrates that the proposed algorithm outperforms other state-of-the-art trackers.

In order to solve synthetic aperture radar image-focus problem when space-variant motion errors could not be ignored, this study proposes a partitioned phase gradient autofocus (PGA) method. In this method, it is most important whether the dominant scatters is in the partitioned images or not. In order to find the dominant scatters, energy gradient factor is defined and energy inflection point is determined. Then, the judgment is made by energy gradient factor and its threshold. Based on measured data processing, it is indicated that the method could distinguish the partitioned images with significant dominant scatters, un-significant dominant scatters, and without dominant scatters. PGA is implemented on all blocks with significant dominant scatters and partial blocks with un-significant dominant scatters. There is no need to use PGA for the blocks without dominant scatters.

In this study, modelling and characteristics analysis of forward scattering coefficients and echoes are investigated. Traditional ground-target forward scattering signal model has not considered the impact of scattering phase; thus it is not accurate enough for describing air-target echoes. To solve this problem, a novel echo model was proposed based on the analytical deduction of complex forward scattering coefficient. The novel model separately expresses the target scattering characteristics and Doppler, greatly facilitating the theoretical analyses of echo characteristics. Then, theoretical and simulation investigations on the amplitude and phase characteristics of forward scattering echoes were made based on the complex forward scattering coefficient model. Theoretical explanations for the periodical fluctuation of far-field echo amplitude, periodical saltation of far-field echo phase, shadow blocking of near-field echo amplitude, and slow variation of near-field echo phase were given, respectively. Meanwhile, the boundary between near-field forward scattering and far-field forward scattering was quantitatively defined, which laid the theoretical foundation for the corresponding signal processing algorithms. Finally, with CST simulation results the accuracy of the echo model is verified and impacts of objects' real shapes are analysed.

Multiple-input multiple-output geosynchronous synthetic aperture radar (MIMO GEO SAR), composed by several mini-satellites in GEO orbits, has more spatial degrees of freedom, which helps to suppress clutter and improves the performance of ground moving target indication (GMTI). However, in order to ensure the satellite safety, the satellite spacing in MIMO GEO SAR is very large. It results in the failure of far-field assumption and causes the moving target defocusing because of the mismatch between the steering vector in far-field sources and the moving target echo. Here, a new signal model based on the near-field sources is first given according to the GEO SAR satellite-ground geometry relationship. Then, considering the phase difference between the different channels, the spatial steering vector is derived and the weight vector for adaptive processing is proposed to suppress clutter and indicate the moving target. Finally, computer simulations are carried out for the validation of the proposed method.

The results of angular and range estimation by conventional signal processing will be far away from true values in the case of unresolved targets due to the merged measurement. In this article, the authors propose a method to localise unresolved targets for frequency diverse array (FDA) radar. Adopting the configurations of subarray-based FDA and full-band FDA as transmitter and receiver, the transmit and receive beampatterns of system are both decoupled in range and angle demands. Furthermore, the receive beamwidth is only a quarter of transmit in range. With the wide transmit beam and narrow receive beam, the authors divide the resolution cell containing unresolved targets into four parts to process separately. A method of intra-pulse beam scanning is proposed to suppress the interference from the targets out of receive beam. Several simulation results demonstrate the effectiveness of the proposed method in the localisation of unresolved targets.

For stationary targets, circular synthetic aperture radar (CSAR) imaging has tended to be mature and perfect. However, for moving targets, due to the long synthetic aperture and the variation of slant plane with the observation angle, the motion compensation is more complicated and has no effective approach. Based on the latest moving target trajectory reconstruction method in CSAR (2015), the polar format algorithm can be improved to image the moving targets when the motion parameters have been estimated. First, the authors placed the imaging reference point on the target to track it, and then compensated for the phase error caused by the incident angle changing and the wavefront curvature. The simulation results of point show that the algorithm is effective and accurate.

A novel method for synthetic aperture radar (SAR) three-dimensional (3D) sparse imaging based on a coprime linear array (CLA) is proposed. To reduce the geometric resolution loss caused by under-sampled sparse SAR, a jointed sparse imaging approach is used. In this scheme, the coprime sampled data of CLA is separately processed via the iterative reweight least-squares approach, and their recovered results are combined to cancel the false targets and grating-lobes to improve the imaging quality. Both simulated and experimented results demonstrate the effectiveness of the method. It shows that the exploiting of CLA and sparse recovery can significantly reduce the linear array antenna amount and the geometric resolution loss compared with the conventional uniform linear array SAR.

The spatial variance of target scattering characteristic would introduce severe impact on the imaging results under the wide aperture for bistatic synthetic aperture radar (BSAR) with navigation satellites. If the isotropic point scattering mechanisms are adopted in image formation processing, the signal-to-noise ratio (SNR) of the image will decrease in such case. Therefore, it is necessary to study the corresponding compensation processing to improve the image SNR. This study proposes an adaptive imaging algorithm to compensate for the spatial variance caused by the target scattering in wide aperture of the system. By using experimental equipment of the research group, the echo data of 1600 s from the scene was collected and processed. Comparing strong scattering area imaging results before and after adaptive phase compensation, the focusing performance is improved. Also thus, the feasibility of wide aperture BSAR imaging based on navigation satellite was verified preliminarily.

Long-time coherent pulse integration method has been extensively used in detecting weak targets, but the detection performance is affected by range migration (RM) due to high radial velocity. This study proposes a new modulation format of chirp radars with stepped frequency and a corresponding coherent integration method based on adjacent cross-correlation operation (ACCO) to compensate RMs of moving targets with, respectively, arbitrary unknown constant velocity. Simulation results show that the method has higher range resolution compared with bandwidth variation modulation and shorter blind distance compared with duration variation modulation.

Distributed digital array radar (DDAR) can operate in multiple modes and perform multiple functions. Compared with traditional phased array radars, the performance advantages of DDAR are obvious in many aspects. One of them is that DDAR can form space mesh in a wide scope. This article proposes a new fast mesh forming method. Unlike traditional multiple beam forming, the authors’ algorithm can form a mesh along range and azimuth. First, the range profile is obtained based on fast Fourier transform. Second, the mesh forming is divided into several steps that are accomplished in polar formatted plane. Finally, the polar formatted result is transformed into Cartesian coordinates. The authors tested the method using RADBASE data, which shows that the authors’ algorithm has good performance.

It is difficult to yield high azimuth resolution of a target in short coherent processing interval, which brings certain challenges for the subsequent three-dimensional (3-D) interference inverse synthetic aperture radar (InISAR) imaging. Aiming at this problem, this study introduces a novel 3-D InISAR imaging algorithm for the target with limited pluses. It is assumed that the received echoes have been compensated and image co-registered, and the variational Bayesian interference can be used to process the received limited pulses to yield the high-resolution 2-D ISAR images. At last, the spatial 3-D image of the target can be reconstructed after combining the interferometric processing and range measurement. The simulation results substantiate the validity of the presented algorithm.

With the maturity of the instantaneous full-polarisation measurement, the instantaneous full-polarimetric system is becoming an important development direction of the polarimetric synthetic aperture radar (POLSAR); however, as an important research branch of the synthetic aperture radar (SAR), the along-track interferometry (ATI) technology for the ground moving target indication (GMTI) is still largely confined to be single polarimetric. In order to facilitate the study of GMTI using a full-polarimetric along-track interferometric SAR (AT-POLINSAR), this study first models the transmitting and receiving signals of AT-POLINSAR and points out its realisability in the existing technical condition of POLSAR. Then, the 6D vector interferometric model for the full-polarimetric echoes is established, where the differences of data processing with the single-polarimetric ATI are analysed. Finally, two simulation methods of the AT-POLINSAR images are given for the generation of signal-level and image-level data, where the results have shown that both the data quality of the interferometric system and its detection performance for moving targets can be improved by the introduction of full polarisation.

The constant false alarm rate (CFAR) detection method based on multi-look polarisation whitening filter (MPWF) has not been obtained in the polarimetric synthetic aperture radar imagery when the texture variable obeys the Inverse Beta distribution. To solve the problem, a new CFAR detection method with analytical expression for false alarm rate is proposed. First, the probability density function (PDF) of the output via MPWF is derived based on the hypothesis of the texture variables obeying the Inverse Beta distribution in the product model. Secondly, the analytical expression of false alarm rate about detection threshold is obtained by integrating the PDF of MPWF output, and the procedure of the CFAR detection method is designed. Finally, the performance comparisons are made among the new method, Wishart CFAR detection algorithm and the two-parameter CFAR method via simulated and real data of AIRSAR. The results show that figure of merit of the new method is the highest and the new method gives the best performance in Inverse Beta distribution case.

A novel polar format algorithm is proposed for spiral trajectory. The synthetic aperture radar (SAR) signal model of spiral trajectory platform is firstly established, then the sector-by-sector phase compensation method of spiral trajectory SAR is proposed. With the descending of the flight platform, the slant range also decreases, thus the sector-by-sector phase compensation is required to correct the quadratic terms of the Range Cell Migration to expand the effective imaging range and eliminate the defocus of the target at the edge of the scene. The 2D-NUFFT is used to transform the 2D wavenumber domain instead of the traditional nearest interpolation method, which decreases the calculation. Finally, the algorithm is validated by simulation.

Video synthetic aperture radar (VideoSAR) technology, which has fine resolution and high frame rate, is used to obtain the dynamic information of the observation scene. However, the height information of the target produces some additional offsets of target location in the digital elevation model under multiangle VideoSAR image sequence. This study analyses the reason for the target location displacement in VideoSAR, which includes the deduction of the mathematical relation between the location displacement and VideoSAR imaging geometry, as well as the influence of target height. Finally, the simulation results validate the theoretical analysis.

In order to solve the problem that radar emitter signal modulation recognition under low signal-to-noise ratio (SNR) has difficulty in selecting the parameters of the classifier and the problem of low recognition rate caused by the improper selection of features, a multi-feature fusion modulation recognition algorithm based on improved particle swarm optimisation (PSO) algorithm is proposed. Firstly, the algorithm uses Choi–Williams distribution time–frequency analysis to transform the radar signals into time–frequency images, and combines transfer learning and principal component analysis (PCA) to extract the transfer features. Then it extracts the Renyi entropy and AR model coefficients of the signals and combines with the image features to realise multi-feature fusion. Finally, the improved PSO algorithm optimises support vector machine parameters so that population converge quickly. The simulation results show that the recognition rate of this algorithm is 95.3% when the SNR is 0 dB. The number of iterations of this algorithm is small, the signal recognition rate of the system is improved, and the effectiveness of the system is improved by applying PCA.

This study considers beam-shape loss (BSL) for pencil-beam digital array radars (DARs), when multiple simultaneous receive beams are formed to cover the volume illuminated by each transmit beam. A general and valid computation procedure for the BSL is derived, and curves of BSL versus average detection probability and transmit beam spacing are given, for various kinds of receive beam arrangements and target types. The results show that the BSL for multiple-beam mode is commonly less than that for single-beam mode. The computation procedure and results are extensions of conventional ones for single-beam scanning radars and would be useful for range calculation and optimum beam spacing determination for modern multiple-beam DARs.

Matrix constant false alarm rate (M-CFAR) detector based on information geometry provides a novel scheme to the detection of target in sea clutter environment for pulse Doppler radar with small bunch of pulses. The detection performance of the existing M-CFAR detectors is greatly influenced by the geometric measures on the matrix manifold. Different geometrical measures lead to different detection performance, some of which are not satisfactory. Motivated by this, the authors utilise Root-Euclidean, Power-Euclidean, Cholesky-Euclidean and new Riemannian measure to design several kinds of detection schemes, which improve the detection performance. Finally, simulation results verify that the designed detectors achieve a better detection performance with a relatively lower computational complexity.

This study proposes a new algorithm for air target radar imaging by taking the geometrical and processing advantages of array antenna systems. The backscattered signal is processed with a new technique to benefit the facilities of angular scanning. In order to virtually increase the number of the radar elements of the array system, a powerful optimal estimator is employed, namely Kalman filter.

The study combines the general hardware platform of the radar system and wireless communication system, as well as applies it in a real detecting scenario. To detect target, the periodogram-based estimation algorithms based on the signal of orthogonal frequency-division multiplexing (OFDM) is introduced. According to range-Doppler (R-D) spectrum, as an enhanced detection algorithm of constant false alarm rate (CFAR), a radar-target detection method, also referred to as binary successive target cancellation, is presented. This research has important theoretical significance for the communication radar-integrated detection technology, and the research results have essential application value for the technology of radar target detection as well as the fusion and development of wireless communication technology.

The interferometric imaging radar altimeter (InIRA) on-board Chinese Tiangong-2 space laboratory is a Ku-band interferometric radar whose major aim is to measure the wide-swath ocean topography. Unlike traditional interferometric synthetic aperture radar (InSAR) aiming at measuring digital elevation model of land surface, Tiangong-2 InIRA adopts small incidence angles and short baseline to get strong and high coherency reflections from ocean surface. The interferometric phase noise is a notable source of errors which limits the accuracy of the ocean height measurements. Compared with traditional InSAR, the height error of Tiangong-2 InIRA shows different distribution pattern due to the absolutely small but relatively large variation incidence angles. This study gives a filtering method for interferometric phase generated with small incidence angles and short baseline. Non-uniform windows are selected according to the relation between the coherence, imaging geometry, and the height variation. Results on Tiangong-2 InIRA data are analysed by comparing the non-uniform filtering method with traditional multi-looking method.

To avoid two apertures adopted in air-borne continuous-wave (CW) synthetic aperture radar (SAR) systems, the novel air-borne linear frequency modulation range interrupted continuous wave (LFMRICW) SAR imaging mode is presented here. Different from the conventional air-borne CW imaging mode, it only requires one antenna to transmit radar pulses and receive its echoes. The system design of this mode is given in detail, and its imaging processor based on a linear prediction model (LPM) is proposed according to echo characteristics. Simulation results on distributed targets validate the presented new air-borne imaging scheme and its corresponding imaging processor.

Segmented discrete polynomial-phase transform (DPT) integrates input signals to enable detection and parameter estimation of weak linear frequency modulated (LFM) signals. However, conventional DPT approaches suffer from a low unambiguously detectable range of the chirp rates because the segmentation effectively reduces the sampling rate between adjacent segments. To enable unique detection of LFM signals with a high chirp rate estimation, the authors propose the use of multiple segmentation sets where the respective segment lengths are governed by a coprime relationship. As such, the ambiguity of the estimated chirp rates that arise from a single segmentation set is eliminated through the fusion of the multiple segmentation sets using the Chinese Remainder Theorem. The effectiveness of the proposed method for the estimation of LFM signals with a high chirp rate is validated by simulation results.

This study designs a micro-machined BCB-cavity patch antenna and two types of four-element micro-machined antenna arrays at 100 GHz. The patches are fabricated on Benzocyclobutene (BCB) polymer material. The silicon substrate is selective lateral etched under the patch antenna to fabricate a cavity surrounded by metal and filled with BCB material. The BCB-cavity under patches can reduce the excitation of surface waves and enhance the radiation on performance. A single large BCB-cavity is designed to implement the four-element antenna arrays under the consideration of mutual coupling. The proposed single antenna has a 2.8 GHz impedance bandwidth. At 100 GHz, the simulated maximum gain is 6.7 dBi for the single antenna and 13 dBi for the four-element antenna arrays.

Multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) waveform diversity design has drawn extensive attention since it has a great potential in remote sensing. Waveform designing becomes one of the most significant tasks in the MIMO SAR system. In this study, a novel scheme has been proposed to generate four waveforms using an orthogonal frequency division multiplexing (OFDM) chirp waveform. The four waveforms have good auto-correlation properties, ambiguity performance, and a good peak sidelobe ratio. This scheme makes full use of the bandwidth. The orthogonal waveform is demodulated by padding zeros and under sampling in the frequency domain. Simulation results are obtained to validate that more orthogonal waveforms can be produced by our proposal scheme with a comparative performance.

Through-the-wall radar has been used in rescue missions, behind-the-wall targets detection, surveillance and reconnaissance etc. However, through-the-wall radar encounters two major problems in complex environment. One is that the refraction of the unknown wall would distort the through-the-wall image. The other is that the multi-reflection between wall and walls as well as wall and targets would lead to a lot of fake targets. To solve these problems, a multi-path suppression algorithm is proposed in this study. The simulation results show that proposed algorithm can automatically estimate the thickness and dielectric parameter of the unknown wall and give an undistort image, and remove the fake targets due to the multi-path effect.

Millimetre-wave frequency-modulated continuous wave (FMCW) radar is expected to be widely deployed for advanced driver assistance systems (ADAS) and self-driving cars. Considering that automotive radars will be deployed in a huge number of cars in future, inter-radar interference will be a significant problem since inter-radar interference can cause miss-detection and/or false detection of the target. As millimetre-wave automotive radar is not standardised at this moment, it is required to evaluate inter-radar interference among FMCW radars with various chirp-rates and chirp durations. This study describes inter-radar interference analysis in FMCW radars with different chirp rates and simulation results of inter-radar interference to confirm the validity of the interference analysis.

Azimuth multi-channel interferometric SAR (AMC-InSAR) mode integrates the azimuth multichannel high-resolution wide swath (HRWS) imaging technique and high-precision InSAR digital elevation model (DEM) generation technique. More equivalent phase centres are obtained through the azimuth single-input and multiple-output technique, which would provide more azimuth samples. Hence, the reliable and accurate DEM measurement of more wide-swath terrain profile would be obtained. Here, the performance of this AMC-InSAR mode is evaluated theoretically. A new processing method based on measured data for this mode is provided and the results of measured data-processing validate the analysed results and the new method.

In the detection of SAR image of sea targets, the simple statistical distribution models such as Gaussian distribution, normal distribution, Weibull distribution etc. are obviously not suitable for the fitting of the background clutter of missile-borne SAR images. The target of the sea surface in SAR image usually has a heavy tail caused by the sea spike, while the KK distribution can better fit it. A two-stage CFAR detector with KK distribution is designed. The results show that KK distribution can fit the data well and the two-stage CFAR detector based on the KK distribution has good performances.

Circular SAR (CSAR) as a new kind of SAR imaging mode has the advantage of long-time observation. For the moving target, the corresponding parameters of the moving target can be calculated by using the position information from the apparent coordinates of the moving target in these CSAR sub-aperture images. The CSAR sub-aperture imaging algorithms include BP and PFA, and the existing parameter estimation model is established on those well-focused and localised images. However, they account for a substantial computation. Here, an improved algorithm for parameter estimation based on CSAR sub-aperture images obtained by PFA is proposed. The wave-front phase error compensation is abandoned, and a new parameter estimation model is established based on PFA images with geometric positioning error. The computational complexity of the whole process of the algorithm is reduced, and the practicability is improved. The point target simulation shows that the method is effective and accurate.

The geosynchronous synthetic aperture radar (GEO SAR) echo simulation has an important significance for GEO SAR system design and image algorithm verification. The study discusses the main steps of the GEO SAR echo simulation process and the calculation of key parameters. At the same time, because GEO SAR has a high orbital altitude and a long-time delay, the error caused by the ‘go-stop-go’ hypothesis must be taken into account. For this reason, the authors have studied the slant range iterative model without the assumption. It is used to calculate the distance between the satellite and target in the echo simulation. Experimental results show that the method is effective and feasible. Based on this, the space variant characteristics of GEO SAR are analysed in detail. It can be seen that the echo signals do not satisfy the range and azimuth invariance.

Autofocus is an essential step in order to obtain the well-focused synthetic aperture radar image. Compared to the non-parametric autofocus, the parametric way is not subjected to the prominent targets so much. Entropy is widely used in parametric autofocus. It is sensitive to the clutter and not a convex function either. In this article, the authors present a new modified entropy to improve the robust of the parametric autofocus by reducing the number of the local optimal solutions remarkably. During the searching process, the residual azimuth phase error (RAPE) is decomposed as the summation of the polynomials. Of course, the used first derivative of the new entropy with respect to the model coefficients is given in detail. Moreover, for applying azimuth subaperture strategy, the authors remove the linear difference of adjacent RAPE via estimating the Doppler centroid, which is more effective than the map-drift method. Finally, real data experiment validates the authors’ approach.

In view of the lack of applicability of the existing equivalent evaporation duct feature calculation scheme in China's sea area and the requirement of the evaporation duct model test, this study used the actual sounding data in China's coastal areas and studied the applicability of the three computational schemes proposed by J.F. Howell, S.P. Oncley, and G.J. Steeneveld in different sea areas and different seasons by comparing the error and standard deviation. The applicability of the sea area shows that the best calculation scheme for the equivalent evaporating duct feature in the South China Sea is the scheme proposed by G.J. Steeneveld et al., while the optimal calculation method for the East China Sea is the scheme proposed by S.P. Oncley et al.; the seasonal applicability shows that the scheme proposed by G.J. Steeneveld et al. has the best-fitting results in the spring, while in the summer and winter, the scheme proposed by S.P. Oncley et al. fits best. These results provide a theoretical basis for the follow-up study.

Here a dual-polarisation printed dipole antenna for spherical near-field measurements is proposed. The printed dipole employs double-layered structure to obtain low cross-polarisation and uses irregular patch to get wide bandwidth. Two such dipoles are cross arranged to form a dual-polarisation dipole antenna. Simulated results show that the bandwidth is over 72% when VSWR is less than 3, the cross-polarisation ratio is better than 30 dB, the port isolation between two dipoles is better than −26 dB, while good radiation performance is also obtained. All the results above prove that the crossed arrangement structure will not affect the performance of the printed dipole, and the strength of mutual coupling between probes can be neglected.

Adaptive digital beamformer (ADBF) is effective in suppressing unexpected interferences arriving at the antenna array. An ADBF intellectual property (IP) using the floating point data type has been developed with high-level synthesis (HLS) technology. This IP computes the real-time adaptive weights of each sub-array to spatially filter the arriving signals. The design has been validated in a recent airborne flight test and the result demonstrated the effectiveness of this approach.

The multipath transmission has a serious effect on jamming efficiency in a short distance ECM task for wideband ground radars. After the sidelobe gain model for a large antenna is introduced, the characteristics of multipath channel in time and frequency domain are analysed. The statistical characteristics about the amplitude change of the intercepted pulse signals and the occurrence conditions of frequency selective fading are explained. The short time compatibility between reconnaissance channel and jamming channel is used to pre-distort the jamming signal, and the serious influence of multipath transmission on the jamming signal is greatly eliminated. The fidelity of deception jamming on the radar is greatly improved. The validity of theoretical analysis is verified by simulation experiments. It provides an important theoretical guidance for a short distance electronic counter measures (ECM) task against ground radars.

The surveillance channel of passive bistatic radar (PBR) is always interfered by strong direct-path and multi-path clutter signals. Based on the radar polarisation theory and the operation mode of PBR, the cross-polarisation reception can suppress the strong direct-path interference (DPI) in surveillance channel, however, which is far from perfect. By using Digital Television Terrestrial Broadcasting (DTTB) signal, several polarisation diversity reception experiments of PBR are carried out. The performance of DPI suppression is tested in different receive polarisation. The bistatic polarisation scattering properties of the civil aeroplane and clutter are obtained. From experimental results, cross- polarisation reception can suppress DPI instead of helping receive stronger echoes for better detection performance. In order to solve this problem, a non-coherent integration approach in terms of polarisation diversity reception is given and verified by a tracking experiment for civil aeroplanes. It demonstrates that polarisation diversity reception not only suppresses DPI but also improves detection performance of DTTB-based PBR under comparison with the fixed polarisation reception.

Signal detection in coloured Gaussian noise usually requires preprocessing the received signal firstly to remove its correlation, resulting in a complicated calculation process. This study transforms the received signal into the frequency domain for detection and systematically studies both the real part (imaginary part) test and the approximate amplitude test (AAT). The study shows that the detection performance of the former is greatly affected by the initial phase of the signal, while that of the latter is basically independent of the initial phase. Frequency domain detection and the best detection are compared under a Gauss–Markov process, and the simulation results show that the detection performance of the AAT is similar to the best detection. In addition, the calculation of the AAT is obviously improved, so the AAT is easier to be applied in engineering compared to the best detection.

Ionospheric disturbance is one of the most serious factors that limit the accuracy of deformation measurement of interferometric synthetic aperture radar (InSAR) especially for spaceborne SAR systems in low frequency such as L-band. Especially in imaging modes with a large coverage, ScanSAR mode for example, ionospheric disturbance phase screen almost submerges other useful geographical information. In this study, two ALOS-2 (L-band) full-aperture ScanSAR images (October 2015 and October 2016) are used to study ground deformation in Beijing from 2015 to 2016. The split range-spectrum technique is adopted to extract ionospheric distortion. The authors splice the differential interferograms of adjacent subswaths by resampling them to perform the overall ionospheric extraction. Also non-local filtering is used to improve the coherence of interferograms. Spatial deformation distribution that was obtained by differential interferometric synthetic aperture radar (D-InSAR) technique using the two ALOS-2 ScanSAR images is highly consistent with the result obtained by persistent scatterer interferometric synthetic aperture radar (PS-InSAR) technique using Sentinel Tops mode images (October 2015–February 2017). The comparison results show the effectiveness of the ionospheric distortion extraction method used in this study. Moreover, the spatial distribution is also highly consistent with the results before 2014, which means that the deformation trend in Beijing continues.

With the rapid development of wind power generation, the number of installed wind turbine increases rapidly. Research shows that radar echoes from wind turbines may have the potential to distract and confuse the target signal by creating false detection. To solve this problem, this study proposes a method based on orthogonal matching pursuit (OMP) algorithm for clutter mitigation. The algorithm first establishes an echo dictionary matrix and filters out clutter through loop operations. Experiments show that the method effectively filters the clutter of the wind turbine.

Due to the curve of the LEO synthetic aperture radar (SAR) orbit and the rotation of the earth, the high resolution imaging for LEO SAR is always facing the problem of obtaining accurate range history. Meanwhile, with the increase of squint angle, it will take longer azimuth time to meet the same high resolution. In this paper, an improved hyperbolic range equation (IHRE) is presented to model the accurate range history for high squint LEO SAR. First, the state vectors of satellite are used to estimate the Doppler parameters. Then, the improved hyperbolic range equation is recovered based on the estimation of the Doppler parameters. Compared with other existing methods, the superiority of IHRE is more precise in the condition of high squint LEO SAR which can provide sufficient azimuth time for high resolution imaging. The simulation and analysis validate the precision of the proposed range history model.

Here, the authors address the state estimation problem of non-linear systems in the presence of unknown measurement noise (MN) covariance matrix. Recently, a high-degree cubature Kalman filter (HCKF) has been successfully used in the non-linear-state estimation problem with arbitrary degrees of accuracy in computing the spherical and radial integrals. However, the efficiency of the HCKF depends on a priori knowledge of the MN. To improve the performance of HCKF for non-linear systems with unknown MN covariance matrix, the authors proposed an adaptive HCKF, which combines the high-degree cubature rule with the variational Bayesian (VB) method to jointly estimate the system state and the unknown covariance matrix online. Experimental results demonstrate the effectiveness of the proposed filter.

Inspired by the optimisation process of multivariate function, a novel gridless direction-of-arrival (DOA) estimation method based on multivariate function genetic optimisation is proposed. The multivariate function is modelled as the difference between the estimated signal and the observed receiving data. The angles to be estimated are the variables of this function. The variables are calculated by minimising the multivariate function with the help of the genetic algorithm. The proposed algorithm can be seen as the gridless pathway to the traditional on-grid sparse reconstruction algorithm. This algorithm does not need to mesh the space into the discrete grid, so it can reduce the estimation accuracy caused by grid mismatch. Simulation results finally demonstrate the superiority of the proposed approach in terms of DOA estimation precision and computational efficiency over the grid-based sparse reconstruction algorithm.

Ground-based synthetic aperture radar (GB-SAR) is a novel system applied deformation monitoring of buildings, mountains, and mining slopes with the advantages of high-resolution, large-scale monitoring, and fast image acquisition image interval. Most of current GB-SAR systems work in the high-frequency band, without the ability of vegetation penetration. So here, a GB-SAR system used for vegetated area is designed on the carrier frequency and other important parameters under the requirements for vegetation penetration, high-resolution and large-scale imaging. At last, the imaging ability and vegetation penetration ability of the designed GB-SAR system are assessed and verified through simulations and experiments.

In this study, an estimation problem for target directions in the multiple-input and multiple-output (MIMO) radar system with unknown mutual coupling is considered. To exploit the target sparsity in the spatial domain, a compressed sensing-based method using multiple measure vectors is proposed to reconstruct the sparse targets and estimate the target directions and scattering coefficients. Additionally, we also propose an iterative method to estimate the mutual coupling matrices after obtaining the target information, where the sub-gradients are derived theoretically to update the mutual coupling matrices. Simulation results show that compared with the exiting methods, the better estimation performance for both target directions and mutual coupling matrices can be achieved by the proposed method.

Taking into account the respective advantages of synthetic aperture radar (SAR) data and optical data in obtaining object information, this article presents a method for retrieval of soil moisture in grassland based on multi-source data (SAR data, optical data and measured data). First of all, optical data is used to classify the grassland area, and then the SAR data is used to obtain the backscattering coefficient of the grassland area. Finally, the soil moisture under the vegetation cover is obtained through the water-cloud model and the microwave backscatter model. The soil moisture in grassland is retrieved and the retrieval results are compared and validated using measured data. The results showed that the suggested method has better classification precision for complex terrain with densely overlapping scattering mechanisms. This method also uses the measured data to correct the soil moisture, which greatly improves the precision of the results.

A broadband horizontally polarised omnidirectional antenna (HPOA) with stable radiation patterns is proposed. The antenna is composed of two orthogonal broadband HPOA units fed by a wideband power divider. Each HPOA consists of four modified Vivaldi antennas fed by a 1-to-4-way wideband power divider. The four Vivaldi antennas are etched on a circular substrate. The proposed antenna is simulated and discussed. Simulation results demonstrate that the designed antenna obtains a bandwidth of 88.9% from 2.5 to 6.5 GHz with reflection coefficients less than −10 dB, and the antenna gains are higher than 2 dBi in the whole frequency band. The antenna shows omnidirectional radiation feature with ripples less than 4.8 dB in the horizontal plane. The proposed antenna is suitable for 4G-LTE and 5G communication systems.

Phase unwrapping (PU) is one of the important procedures in measuring digital elevation model (DEM) from interferometric synthetic aperture radar (InSAR) images. It is known that the existence of phase discontinuity poses challenges to the traditional PU algorithms. In this study, the authors propose a coupled Markov random fields (MRF) called line process (LP) for PU, abbreviated as the LP-MRF method. First, an 8-neighbourhood line process is used to detect discontinuous phase surfaces while regularising continuous phase surface. Then, a truncated quadratic is utilised in the LP model for optimisation convenience. Finally, the proposed method on four types of simulated experimental data is tested, which yields that the proposed method has better performance than some of the commonly used methods in handling sharp phase discontinuities while regularising continuous phase surfaces.

Based on the purpose of proactive anti-reconnaissance, the essential characteristics of several typical pulse repetition interval (PRI) sorting algorithms were analysed and the feasibility of counter-deinterleaving was discussed. A method for disturbing arrival time sequence by using interference pulse was proposed, which changes the statistical properties of the radar PRI to disturb the deinterleaving results. The simulation results show that the pulse jamming method proposed in this paper can influence PRI sorting process effectively, which let signal processer make a misjudgment on PRI pattern of radar.

Spaceborne bistatic multichannel synthetic aperture radar (MC-SAR) system employed inclined geosynchronous Earth orbit (GEO) transmitter and low-Earth-orbit (LEO) receiver can provide fine spatial resolution and a vast area of surveillance, which presents great potentials for future Earth observation. Nevertheless, owing to special geometry and big differences of orbital characteristics, the conventional effective phase centre (EPC) operation for unambiguous SAR signal reconstruction cannot be directly used. To address the issue, starting from geometry model of GEO-LEO bistatic MC-SAR, the new effective positions of the receiving channels are obtained. Then, the time-variant characteristics of residual phase error after the presented EPC processing is analysed. Finally, the method of reconstructing unambiguous SAR signal is presented. Simulation results show the validity of the proposed method, which can efficiently reconstruct the unambiguous signal for GEO-LEO bistatic SAR.

Fast estimation of ship velocity remains a significant gap in ocean applications despite the increasing interest in space-borne synthetic aperture radar (SAR). This study proposed a fast velocity estimation method for moving targets based on complex SAR image. Here, the authors first applied several defocusing filters to the imagining results, estimating the along-track velocity of all moving targets by discerning the differences in the maximum of the filtered images. They then derived the cross-track velocity based on Doppler centroid drift. The results showed that the proposed method is effective in real TerraSAR-X dataset and is able to estimate velocity for moving targets in SAR complex image.

In order to achieve weak target detection, the range migration and Doppler frequency spread induced by the target motion within the coherent processing interval should be compensated to focus the target energy in a certain range-Doppler cell. This article proposes a new integration method based on non-uniform Keystone transform and non-uniform fast Fourier transform (NUFFT) for random pulse repetition interval (PRI) radar. In this method, non-uniform Keystone transform is applied to correct the linear range migration. After that, the acceleration is estimated by dechirp process and the Doppler frequency spread is compensated. Finally, the target energy is accumulated coherently via NUFFT. Compared with the random PRI generalised Radon-Fourier transform (RPRI-GRFT) and the moving target detection method for random PRI radar, the proposed algorithm achieves a good balance between the detection performance and the computational cost. Simulation results are provided to demonstrate the effectiveness of the proposed method.

Target localisation using frequency diverse array (FDA) has drawn much attention owing to the additional degree of freedom in the range dimension. However, the Doppler effect was often ignored in previous FDA works because of the stationary target assumption, and in contrast, even stationary target localisation could be of quite a high computational complexity. In this study, a method is proposed that can jointly estimate range, angle, and Doppler for FDA multiple-input-multiple-output radar with low computational complexity. First, Doppler is estimated independently by utilising unstructured maximum likelihood method. Next, traditional two-dimensional (2D) MUSIC is divided into multiple one-dimensional (1D) MUSIC to estimate the angle. Then substituting the estimated angle into the former 2D MUSIC results in a 1D searching over range dimension to get the range estimation. The advantage of the proposed method was verified by simulation results.

A precise motion compensation method is proposed to achieve very-high-resolution synthetic aperture radar (SAR) image. The very-high-resolution is designed to achieve higher than 0.1 m resolution. For very-high-resolution SAR with wider integration angle, it implies that there exists phase error caused by the squint angle. Further, the phase error between the margin and the centre of the beam is azimuth variant. The proposed two-step motion compensation method can effectively overcome the shortcomings of the normal method and achieve. The real data results with well-focused very-high-resolution SAR images demonstrate the effectiveness of the method.

Synthetic aperture radar (SAR) has a good ability to detect the microwave scattering characteristics of the target and has a good capability of slant range Doppler positioning. Using multi-view SAR images in combination with image matching and positioning equations, the 3D position of the target can be obtained. In the past, multi-view 3D reconstruction mainly used side-looking images with parallel trajectories but different incident angles. That method is not universal for different configurations and lacks analysis of the relationship between solution and parameter error. This study aims at the problem of multi-view SAR 3D reconstruction. The authors establish general 3D reconstruction equations that can be used for non-parallel track and non-side-looking and the solution method is deduced. Based on this, an analysis method of error sensitivity is proposed and the dependence relationship between the reconstruction error and configuration, velocity, position, and slant range is analysed. The correctness of this method is verified by simulation experiments, which provides guidance for selection of configuration and sensor accuracy when applying 3D reconstruction.

Synthetic aperture radar (SAR) monopulse angle measurement is an adequate method of target angle measurement in low signal-to-clutter and noise ratio. However, there is a contradiction between the instantaneous angle measurement and the SAR coherent accumulation. In this study, the authors use the total variation method to solve the above problem, and propose the monotone iterative method to enhance the efficiency of the total variation method, which is verified in the simulation.

Sparse method provides an efficient way for antenna systems to achieve low cost, weight, and complexity. However, the synthesis of sparse arrays always limited to multiple constraints, which include aperture, number of elements, and minimum elements spacing. The characteristic that element number in each ring of concentric ring array (CRA) is related to its ring radius, which is different from square or rectangle planar arrays, leads to a complex constrained optimisation problem for the synthesis. Here, a novel vector mapping method for e-design of sparse CRA is proposed. According to the mapping functions established here, the ring radius and element number can be mapped by two variable vectors with only upper and lower boundaries. Thus, the strong constrained optimisation problem can be transformed to the unconstrained. Numerical examples show the effectiveness of the proposed method, which provides layouts of elements able to produce lower sidelobe level that satisfy multiple requirements.

The target localisation in a multistatic passive radar system using bistatic range measurements from multiple transmitter–receiver pairs is considered. A novel closed-form solution employing multidimensional scaling (MDS) analysis technique is proposed, which is based on the optimisation of a cost function related to the scalar product matrix in the classical MDS framework. The proposed solution is robust to large measurement noise. Simulation results demonstrate the proposed solution achieves a significant performance improvement over existing spherical interpolation, spherical intersection and two-step weighted least squares methods, and attains the Cramer–Rao lower bound at a relatively higher measurement noise level before the threshold effect occurs.

A two-dimensional (2D) direction-of-arrival (DOA) estimation method for coherently distributed (CD) sources has been proposed in high real-time situation using only one snapshot. Utilising two uniform linear arrays (ULAs), the proposed algorithm first construct four equivalent matrices with rotational structures using one snapshot, and then a total equivalent covariance is extended by the four matrices. Finally, two rotational invariance matrices can been calculated by ESPRIT-like algorithm, and the eigenvalues which contains of the information of the central DOAs can be obtained by eigen-decomposition of the two matrices. To improve the performance of the proposed method, in-phased accomplished data is proposed. Without snapshots accumulation, peak searching, and correlation process, the 2D DOA estimation method for CD sources can be used for real-time situation. Several simulation results are used to illustrate the performance of the proposed method.

Synthetic aperture radar (SAR) can provide high-resolution two-dimensional radar images of the target area. The error of the altitude between aircraft and the target area causes geometrical distortion of the SAR ground image, which is unfavourable for scene matching and target recognition. Existing methods, such as radar altimeters, work in the case of vertical beam irradiation. However, the highly accurate aircraft altitude estimation for SAR (under oblique irradiation) is still a challenge. In this paper, an aircraft altitude estimation method based on multi-beam pitching sum and difference channels radar echoes is proposed. The pitching sum and difference channels angle measurement principle is used to achieve accurate beam centre distance estimation, and the cyclic multiple beams are used to realise the estimation of the grazing angle deviation. Therefore, this method can realise the accuracy estimation of the aircraft altitude under oblique beam irradiation conditions. Then, the effects of various error sources on the accuracy of altitude estimation are analysed. The results of simulation and real data verify the correctness of the analysis and the validity of the proposed method.

Tiangong-2 interferometric imaging radar altimeter (InIRA), the first space-borne radar altimeter in the world, applying a new mechanism of interferometry with short baseline and small incident angle, can achieve wide swath and high accuracy sea surface height measuring. Comparing to traditional altimeter, InIRA can obtain SAR image of observation area, which means InIRA needs higher AD sampling rate. Due to the limitation of satellite on-board storage and downlink speed, in order to extend the working time of InIRA, data compression algorithm for InIRA must be studied. Block adaptive quantisation (BAQ) is an efficient and widely adopted approach for space-borne SAR raw data compression. Based on the characters of InIRA echo waveform, this study discusses compressing InIRA raw data by changing quantisation bits and size of blocks of BAQ algorithm to achieve higher compression ratio and less sea surface height error.

A new sea-level elevation measurement system was introduced, which uses a distributed multi-base forward-scattering mechanism. After introducing the working principle of the system, this study analyses the main influencing factors of relative elevation measurement in detail. It is proved through quantitative expression that the interferometric phase error is the main error source affecting relative elevation measurement. In order to evaluate the system capability and prove that the multi-base InSAR (MbInSAR) can meet the application requirements of gravity field inversion through relative ocean surface elevation measurement, three aspects of decorrelation, geometric decorrelation, volumetric decorrelation, and SNR decorrelation, are analysed as the interferometric phase error sources.

To achieve well-focused ISAR imaging with low signal-to-noise ratio (SNR), this study constructs a statistical model and derives an effective method for image autofocusing based on Bayesian inference. Particularly, hierarchical sparse-promoting priors are imposed on the weights, which are conjugate to the likelihood. The method has closed-form solution which facilitates computation. Experimental results have demonstrated the effectiveness of the method in low SNR and short aperture scenarios.

Various techniques have been proposed in the literature to tackle the problem of moving target detection in the low-earth orbit synthetic aperture radar (LEO SAR) scenarios. Nevertheless, this issue has not been addressed yet in the geosynchronous synthetic aperture radar (GEO SAR) situation. This study points out the existing differences in the Doppler domain between GEO and LEO SAR imaging, and shows the advantages of using Doppler spectrum based-techniques to solve the multiple ground moving target indication issue in GEO SAR. Furthermore, it provides a new formulation for the moving target Doppler centroid in the GEO SAR case that consider the specific features of the GEO SAR imaging. Simulation results are provided to demonstrate the accuracy of the developed expression.

In this study, the near-field beam focusing algorithm of reconfigurable reflect array for security imaging application is proposed. The proposed near-field focusing algorithm is based on classic array method, which is usually adopted for far-field pattern calculation. In order to satisfy the near-field imaging application, the imaging distance is added to array method, and the improved formula can calculate the shifting phase of every array element precisely. In addition, due to discrete phase characteristic of reconfigurable reflect array, a phase choice method based on trigonometric function is used in authors’ design. Based on the proposed algorithm, the shifting phase of every element is calculated and obtained the simulated beam focusing patterns. Meanwhile, the calculated shifting phase is written to whole array by field-programmable gate array, the near-field beam scanning patterns is measured and the measured results are in good agreement with the simulated ones.

Phase unwrapping (PU) is a key step of interferometric SAR signal processing. The accuracy of the unwrapping phase directly affects the accuracy of the digital elevation model (DEM). The traditional path-integral methods and global-planning methods cannot take into account both PU accuracy and processing efficiency, and causes PU error diffusion and large-area PU holes. To solve these problems, this study proposed an improved PU strategy based on dynamic adjacent table. For the problem of unwrapping holes that appears in traditional path-integral methods, this study introduces improved local quality maps to guide the path-integral operation, which effectively realises the phase compensation of the PU holes. For the low efficiency of the traditional branch-cut algorithm, this study implements the real-time integration path optimisation planning by further introducing the dynamic adjacent table and greatly reduces the data volume of the adjacent table. Thus, the efficiency of PU was greatly improved. Finally, the proposed method was validated by the airborne dual-antenna interferometric SAR experimental data.

There are a large number of high-energy particles in the space. These high-energy particles induce a single-event upset effect on DSP, FPGA, and other programmable digital controllers inside the beam-steering unit, which can produce unpredictable and erroneous influences, thereby reducing the reliability of space-borne-phased array radars. In order to solve the above problems, this study presents a design of beam-steering unit based on a kind of application-specific integrated circuit (ASIC). By using the advantages of ASIC circuits such as strong radiation resistance, high integration, and low power consumption, this solution adopts an anti-irradiation ASIC chip as a controller, and anti-irradiation RS422 transceivers are used to complete interface conversion for receiving data and transmitting data. The beam refreshing and telemetry functions between the beam control computer and the 24 microwave modules are realised finally. The test result shows that the phase distribution time is <30 μs when the clock is 3.125 MHz, and the falling edge of sampling pulse is located at half the length of a data symbol, ensuring data hold time long enough to sample correctly.

An effective Max-Fire CNN model MF-SarNet for synthetic aperture radar (SAR) automatic target recognition (ATR) is presented, here. By selecting the convolution kernel of the Fire module in the network, the parameters are reduced to obtain the effective convolutional neural network of less parameter. In view of the requirement of deep learning for large-scale data, an augmentation method is proposed, which can learn the features of large database better. The results based on MSTAR database show that the model is effective and the result is encouraging. The accuracy of SAR image recognition is 98.53%.

Polar format algorithm (PFA) as is an efficient algorithm can be well applied to spotlight bistatic synthetic aperture radar (SAR). However, a planar wavefront assumption which leads to image distortion is made. In this study, a new method to compensate for the wavefront curvature of PFA image is presented and it can well correct the defocusing effect and geometry distortion even under arbitrary platforms paths. By projecting the coefficients of Taylor expansion from the azimuth-time domain to wavenumber domain, the new method does not need repeated interpolations to construct the compensation filters for all the errors, which can decrease computational expense in a way. Finally, the effectiveness of this method is verified by numerical simulation.

Elimination of spatiotemporal bias of asynchronous multiple sensors is the foundation of accurate multi-sensor data fusion. In this article, a sequential processing simultaneous spatiotemporal bias and state estimation algorithm for asynchronous multi-sensor system is proposed. The spatiotemporal bias is combined with target state to obtain an augmented state vector, and the augmented state model is formulated. For asynchronous multi-sensor with known but different sampling periods, a sequential processing method is proposed to handle the multiple measurements. The relationship of sensor measurements, target state and spatiotemporal bias is analysed, and the corresponding measurement model is formulated. A novel algorithm, in which the unscented Kalman filter is used to handle the nonlinearity between the augmented measurement and state vectors, is proposed to jointly estimate the spatiotemporal bias and target state. Simulation results verify the effectiveness of the proposed algorithm.

Here, the authors use the K-Shape algorithm, which is based on a z-normalised version of cross-correlation distance measure, to extract change patterns from time series synthetic aperture radar (SAR) images. These change patterns focus only on the shape of time series, rather than amplitude and phase. Besides, they employ a simple and elegant method to choose the optimal number of clusters. Experimental results on multi-temporal SAR images of Shanghai indicate the effectiveness of their approach.

This article presents an integrated design of active phased array for low-altitude detection radar. Integrated design is an important method to realise miniaturisation and low cost. The multifunctional integrated chip technology is used to design the tile-type transmit/receive module. The whole array is divided into subarrays for modularisation. In addition, in order to be integrated with active circuits, a wide-beam and silicon-based antenna is proposed and verified.

Radar coincidence imaging (RCI) is a recently developed staring imaging technique based on the wavefront random modulation and temporal–spatial stochastic radiation field. Before coincidence imaging processing, the RCI needs to compute the reference matrix accurately. Unfortunately, model error usually exists, which degrades the imaging performance considerably. In this article, by exploiting the sparse prior of target, the authors propose a sparsity-driven autofocus imaging via iterative maximum a posteriori (SA-MAP) algorithm for the RCI when model error exists. The algorithm performs well via simultaneous sparse imaging, self-calibration and parameters update. Simulation results demonstrate the validity of the proposed algorithm and performance improvement over the existing algorithms.

In passive radar network (PRN), the receiver placement optimisation which has the ability to improve the coverage performance attracts much attention recently. In this study, the K-coverage performance is considered since the pre-condition of deghosting in a radar network is that the target has to be covered by bistatic pairs. Thus, a K-coverage-based receiver placement optimisation is formulated, in which a weighted M-centre model and the required radar cross section (RCS) for target detection are involved. Moreover, in order to solve this high dimensional optimisation problem, an iterative method which is based on K-order Voronoi algorithm and neighbourood search is proposed. Finally, the proposed method shows its effectiveness in solving the K-coverage optimisation problem of PRN via simulations. Specially, the probability of K-coverage is up to 99.8% with the optimal placement.

The abundant space, time, frequency and code resources of distributed multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) enables it to bring various applications. The generalised ambiguity function (GAF) of distributed MIMO SAR is analysed. By equating the bistatic SAR to equivalent phase centre (EPC), the GAF can be expressed as sum of that of mostatic SAR. The influence of EPC's position on GAF is analysed, including its effects on amplitude items in range direction, in azimuth direction and phase item, and the boundary conditions of formation scale within which the envelope items are not affected are deduced. Furthermore, the phase in GAF is expressed as linear combinations of EPC position related to formation centre. The simulation results verify the negligibility of formation scale and show that the linear combination expression is accurate enough to evaluate the resolution.

In general, conventional synthetic aperture radar (SAR) imaging algorithms focus SAR images for stationary targets. However, in the case of moving targets, the motion of the targets induces an undesired range variation which makes the obtained SAR images to be dislocated and defocused. Therefore, in this study, the authors propose a method that effectively focuses the SAR images for the moving targets and estimates their motion parameters with single-channel SAR system. The proposed method consists of the following three steps: (i) direct exploitation of the range variation from the echo signal, (ii) range cell migration compensation with the estimated range information, and (iii) Doppler compensation and parameter estimation. The simulation results demonstrate the robust performance and high computational efficiency compared to the conventional moving target imaging algorithms.

Aiming at the problem of large amount of calculation and long recognition time of traditional method of modulation identification of centralised multiple-input multiple-output (MIMO) radar signal, partial zero-delay instantaneous autocorrelation spectrum is proposed to identify the modulation of centralised MIMO radar here. In this method, the modulation identification of the centralised MIMO radar is performed by extracting the ratio of the sub-peak to the highest peak in the zero-delay transient autocorrelation spectrum of the part signal. The computational complexity of this method is low, and it identifies without additional features for coded MIMO radar signals. Here, the definition of partial instantaneous correlation spectrum is given; the feasibility of using this method to identify the modulation type of the centralised MIMO radar is analysed, and the identification process is discussed. It is showed that the proposed method can shorten the recognition time while guaranteeing the detection performance under a certain SNR in the simulation results.

Bird flight has caused many scientists' interest for a long time, of which the flapping is the most common locomotion. Radar provides a powerful tool to observe birds' migration. Aerial birds can be characterised by their electromagnetic scattering characteristics and the radar cross-section (RCS) is one of the most important characteristics. The wings' attitudes of flying birds may induce the RCS values fluctuation; thus the authors can extract the flapping attitudes from the RCS values. In this article, a method of simulating the electromagnetic scattering characteristics of airborne birds was proposed, based on which the flapping attitudes of flapping birds in actual flights were extracted. First, electromagnetic scattering models of a flying bird with different flapping attitudes were built and the FEKO electromagnetic simulation software was used to obtain the bird target's electromagnetic scattering characteristics. Then, the relationship between the flapping angles and the RCS values of the model was studied and the parameters of the flapping angles model were estimated using a parameter estimation method. Finally, based on the measured data, the flapping attitudes of the bird in actual flights were extracted and the accuracy of the scattering model was validated.

Integrated radar and communication system can significantly enhance the work efficiency and considerably occupy less hardware resources. However, the integrated systems have limited supply resources, where a proper scheduling scheme is needed to meet the requirement of systems. Here, the authors propose a task-scheduling scheme based on the greedy algorithm, where each arrangement is the result of selecting the minimum shift time compared with the expected time. By guaranteeing the best result of each task, the minimum average time shift ratio (ATSR) of the whole tasks is obtained. Simulation results show that when the number of the tasks is quite large, the proposed scheme has more advantages than the traditional scheme based on time pointer algorithm. Authors’ proposed scheme can significantly reduce the average offset time of tasks while maintaining a satisfactory successful scheduling rate (SSR), which shows more advantages in the integrated systems.

In this study, a new set of hybrid orthogonal frequency division–linear frequency modulation–phase coded (OFD–LFM–PC) waveforms are proposed to improve the detection performance of multiple-input-multiple-output (MIMO) radars. In the time domain, the inherent sidelobe properties of the spatial synthesised signal of the hybrid OFD–LFM–PC waveforms are analysed. In the space domain, the transmitting power pattern of the designed waveforms is derived. The influence of the modulated PC sequences on the temporal and spatial properties of the proposed waveforms is also studied. The proposed waveforms can suppress the temporal sidelobes greatly and obtain almost omnidirectional transmitting power pattern which is preferred for target detection in wide area. Simulations demonstrate the superiority of the proposed waveforms over the commonly used OFD–LFM waveforms.

When there is sidelobe interference in the array pattern, adaptive monopulse angle measurement can suppress interference and improve the accuracy of angle measurement. However, when the interference occurs in the mainlobe, the angle measurement performance will be seriously deteriorated. This problem can be solved well with the monopulse angle measurement algorithm based on auxiliary array. Here, auxiliary array radars are added to the main radar to extend the aperture of the array, and using the MSINR criterion or MMSE criterion to suppress the mainlobe interference, a good measurement accuracy can be obtained. The effectiveness of the method is proved by computer simulation.

In this study, a novel high-isolation wideband divider based on multi-layer elliptical defected ground structure coupler is presented along with its analytical theory and design procedure. The proposed divider could be conveniently applied for high- power applications with less loss for the absence of isolation resistors. The simulation results show that in 3.1–10.6 GHz, the return loss S₁₁ and S₂₂ are <−15 dB, the overall isolation S₂₃ is <−20 dB and the best part achieves−50 dB. Insertion loss S₂₁ and S₃₁ are both >−4 dB within 4–9 GHz, and the amplitude and phase difference between port 2 and port 3 is <1 dB and 2°, respectively.

This study introduces a special converted measurement Kalman filter (CMKF) algorithm which apply to satellite for tracking target. Typical CMKF applies to radar which measures targets in spherical coordinate system. The new algorithm can be used by satellite which measures target's latitude and longitude. Improved CMKF algorithm tracks target in simple situation but is not able to deal with multi-target and information missing situation. Multiple hypothesis tracking (MHT) can track multi-target accurately and has the ability to initial track and end track at all times. For satellite, MHT use improved CMKF to calculate cost matrix and update the state estimate and estimate covariance. In the simulation, tracking process is simulated by MATLAB. Single target measured by satellite can be tracked accurately by CMKF algorithm. MHT can track multi-target accurately and distinguish the information missing rightly.

Fast ship contour extraction in synthetic aperture radar (SAR) images plays an important role in sea surface surveillance. Ship contours and sizes and shapes extracted from them are salient features in ship classification and recognition. This study presents a two-step method to fast extract ship contours. At the first step, an existing object detection method is used to extract bounding boxes of ships. Next, the morphological operators are applied to each box to yield a compact external contour. At the second step, using the compact external contour as the initial contour, the active contour algorithm is used to iteratively generate ship contours. Owing to compact initial external contour, the active contour algorithm avoids the topological merging and splitting, two time-consuming operations. In this way, ship contours can be fast extracted.

This study introduces a novel insect speed extraction method based on a high resolution and full polarisation radar with vertical-looking mode. The insect echo model of the high resolution and full polarisation radar is first established. Then, an iterative algorithm for estimating the horizontal speed of insects is derived based on the second-order polynomial approximation. Finally, experimental results show the effectiveness and feasibility of this algorithm in extracting the horizontal speed of insects. Compared with the traditional method, the method here is more simple and effective and greatly reduces the computation.

Here, it is aimed to measure and detect the iron mass of a concrete solid wall, column, floor by using of ultra-wide band radar. Electromagnetic waves boundary conditions, reflection, and refraction of waves that radiate in solid material are analysed. GPR imaging methodology and scanning types such as A, B, and C are analysed. Ultra-wide band radar imaging is used for detecting measuring the diameter of the iron material.

Multiple-input multiple-output (MIMO) radar is a novel radar system which can achieve more individual observation echoes than the number of the actual antennas by transmitting orthogonal waveforms. At present, pattern theory is usually utilised to evaluate the azimuth imaging indicator of the MIMO imaging radar system. Although it cannot describe the two-dimensional performance, it is quite effective to analyse the azimuth resolution of far-field targets. However, the pattern based on the far-field condition becomes invalid for targets in the near-field area, thus it cannot explain the appearance of near-field azimuth grating lobes. In this article, spatial spectrums and generalised ambiguity functions (GAFs) of near-field targets are calculated. By describing the near-field GAF (NGAF) approximately, the relationship between the distortions of NGAF and the spatial spectrum is studied qualitatively, which can explain the appearance of azimuth near-field grating lobes. In addition, the calibration method of amplitude and phase errors by an isolated corner reflector is presented in this article. Finally, a simulation and an experiment are carried out to verify the conclusions.

Multiple-input multiple-output (MIMO) radar plays a more and more important role in radar imaging, target detection, and other fields owing to its unique array structure. Transmitting orthogonal signals by different transmitters, a MIMO radar can significantly enhance the azimuth resolution. It forms multiple observation channels from different transmit and receive array elements, achieving an equivalent large aperture in azimuth direction. However, the amplitude and phase errors in each channel are introduced, which will lead to inferior imaging performance of the system, especially in azimuth direction. To solve this problem, a method to estimate the amplitude and phase errors of each channel based on a strong scatterer is proposed here. Peak amplitude of one-dimensional range between channel is estimated using constrained least square (CLS) based on ideal point target characteristics. It proved to be valid by a simulation and an imaging experiment.

Moving ships imaging is an important issue in marine remote-sensing by spaceborne synthetic aperture radar (SAR). As the moving ships defocus generally in high-resolution spaceborne SAR images, the refocusing step is demanded for the following processing in classification and identification. A new refocusing method based on Doppler parameters search is proposed to enhance the performance of ship images. This method is applied directly on the single-look complex image data. Furthermore, the space-variant characteristic of Doppler parameters is taken into account within this method. Finally, the GF-3 satellite SAR data refocusing results of moving ships verify the effectiveness of the proposed method.

Detecting ground moving target in bistatic forward-looking synthetic aperture radar (BFSAR) has become increasingly important in military and civil field. Compared with pulse Doppler radar, the long observation time and high resolution of BFSAR will lead to three problems in the received signal: Doppler ambiguity, large range cell migration and Doppler cell migration, which tremendously aggravate the difficulty of ground moving target detection (GMTD). In this study, the authors propose a three-step ground moving target detection method for BFSAR to solve these problems and achieve good performance on GMTD. First, the bulk-deramp filtering and Keystone transform are exploited to suppress Doppler ambiguity and correct range cell migration, respectively. Then, time-division space–time adaptive processing is utilised for clutter suppression, which eliminates the effect of the Doppler cell migration. Finally, modified Wigner–Ville distribution method is applied to further improve the signal to clutter and noise ratio and the moving target can be detected in the integration domain. Simulations are carried out to demonstrate the effectiveness of the proposed method.

Based on a pair of linear frequency modulation waveforms with opposite slopes, the mathematical model of the influence of intermediate frequency deviation (IFD) and sampling frequency deviation (SFD) on simultaneous polarisation measurement is derived. An IFD and SFD joint estimation and calibration method is proposed in this article. Simulation and real data results show that the radar frequency stability can change the position and phase of the polarisation scattering matrix (PSM) measurement. The approach proposed in this article can regulate the peak deviation effectively, compensate the phase error and accurately acquire the four elements of PSM.

The adaptive beamforming is one of the key techniques for array signal processing. However, the matrix inversion operation in the existing methods will cost a large amount of computational complexity, which results in poor real-time processing ability. In order to reduce the amount of computational cost, a fast and robust adaptive beamforming method based on complex-valued radial basis function (CRBF) neural network is proposed. In the proposed method, the CRBF neural network is established, thus the direct matrix inversion is avoided by the nonlinear mapping processing from the array covariance matrix to the adaptive weight vector, and therefore the calculation speed of adaptive weight vectors is increased. Based on the simulation results, the proposed method is verified that the speed of adaptive beamforming is increased compared with sample matrix inversion (SMI) algorithm method and an improved performance is achieved compared with that of conventional real-valued RBF neural network beamformer.

An equivalent circuit model of double hexagonal loops frequency selective surface (FSS) was established. The formulas of LC parameters were proposed with equivalent repetition period. The reflection frequency, transmission frequency, and the location of first modal interaction null were simulated, and the results showed a good agreement in full-wave simulation result. On this basis, an ultra-wideband composite absorbing material (CAM) was proposed, and its equivalent circuit model was also established. A sample was fabricated and measured to verify the validity of the model. The results showed a good ultra-wideband absorbing performance in the range of 1.9–8.9 GHz.

Multiple-input multiple-output (MIMO) imaging radar is a new kind of new imaging radar in recent years. It can achieve faster data acquisition speed than the traditional ground-based SAR due to the ability to get a large number of multi-channel data in a short period of time. However, traditional single-core digital signal processors (DSPs) have limited space and ability to deal with such large amount of data. To solve this problem, a real-time image processing software architecture for MIMO imaging radar algorithm is designed and carried out based on TMS320C6678 DSP of Texas Instruments (TI), which is the highest-performance fixed/floating-point DSP based on TI's KeyStone multicore architecture. The efficient imaging algorithms mapping from Matlab to DSP is realised, with efficient task allocation, resource reuse of echo data, and processing variable, and using the method of multicore parallel processing.

The low, slow, and small (LSS) target detection has always been a problem for both ground-based and air-borne radar systems. The factors such as weak target reflection energy, ground clutter, and random Doppler component will have a severe impact on radar detection performance. In recent years, researches on multiple-input multiple-output (MIMO) radar system have achieved great progress. By utilising multi-channel and multi-waveform technology, MIMO radar can form equivalent phase centres and virtual apertures to provide more system freedom and enhance detection performance. To address the LSS target-detection problem, the authors propose a novel Doppler division multiple access (DDMA) MIMO radar system, which employ DDMA waveform to ensure the orthogonality of the transmit signal and avoid some of the problems in the application of frequency division multiple access (FDMA) and code division multiple access (CDMA) for the actual radar system. The sparse array is employed to supress the grating lobe of the beam pattern and improve the angle estimation performance by optimising the position of the antenna array elements. Finally, the architecture of the designed radar system is introduced and the results of the detection performance to LSS targets based on real measured data is given.

Conventional space-time adaptive processing (STAP) achieves clutter suppression by combining spatial signals and the temporal pulses. However, extreme slow-moving target cannot be effectively detected by space-time joint filtering in ambiguous and non-broadside clutter environment for airborne-phased array radar. By increasing the polarisation information in clutter suppression, improved moving target detection performance can be obtained by the polarisation-space-time adaptive processing (P-STAP). In this study, the performance of P-STAP for airborne-phased array radar is analysed. The polarised signal model of airborne-phased array radar is firstly established and then clutter suppression principle of P-STAP is derived in detailed. Afterwards, the performance of P-STAP is investigated and compared with conventional STAP in ambiguous clutter environment. It is verified that the P-STAP can outperform the conventional STAP for slow moving target detection by three-domain joint processing, especially for ambiguous and non-broadside clutter environment for airborne-phased array radar.

With the development of synthetic aperture radar (SAR), it is more and more important to recognise the image obtained by SAR. SAR is a useful tool for geoscience and remote sensing, and there are a large amount of SAR images and products. How to quickly identify and process this massive information in the shortest time and find the target in time is the focus of research in this field. In the traditional processing method, the digital processing is used. It is time and storage consumption due to its massive data. This study proposes optical methods for target recognisation of SAR images. In this method, it takes the advantages of high speed and high resolution in optical processing methods to solve the bottleneck encountered by traditional methods. The method is based on an optical correlator. The optical processing method has a large capacity for a single processing and has a great advantage over the simple calculation method in processing speed. The experimental results demonstrate the effectiveness of the optical processing method.

The classic method of testing array antenna is measuring the beam pattern separately, which suffers from low efficiency. In this study, a fast measurement method used for received array antenna has been present. Firstly, the patterns of element antennas have been tested using multi-channel receiver. Then the entire pattern could be computed by weighting the information of elements. The information contains amplitude and phase, which could be obtained by theory or measurement.

According to the structural characteristics of non-uniform dual circular array (NDCA), a new method is proposed to solve the problem of mutual coupling error. In this algorithm, solving the mutual coupling problem of NDCA can be equivalent to solving that of non-uniform linear array (NLA). Firstly, the mutual coupling matrix is divided into several blocks. Then, each sub-block can be decomposed into the sum of several matrices with special characteristics by matrix addition method. As a result, the signal angles and mutual coupling coefficients can be conveniently decoupled. Compared with the iterative self-calibration algorithm, the proposed algorithm has a small amount of calculation. Moreover, it neither requires any prior information nor has problem of local convergence. The new method can accurately estimate the signal directions and mutual coupling coefficients.

Baseline is the key factor for highly accuracy terrain elevation measurement in InSAR system. Variation of baseline attitude induced by aircraft's unstable motion leads to phase errors varying along the aperture. The variation will generate prodigious deterioration in DEM's precision. Therefore, in order to reduce the phase errors, critical motion compensation has to be implemented. Here, the sub-aperture method is introduced to resolve the above issue. The new method is described with mathematical analysis and modelling. The influence of the new method on the sensitivity of roll estimation is also analysed. The simulation and real testing show a very positive result. The roll errors are eliminated greatly in case the sub-aperture length is optimised. Moreover, the requirements of SNR and azimuth resolution are satisfied.

YaoGan 13 (YG-13) represents the most advanced Chinese synthetic aperture radar satellite currently in use. This paper reports on experiments conducted to assess the slant-range accuracy of YG-13. Error sources in the YG-13 ranging system, such as atmospheric path delay and the internal electronic delay of the instrument were analysed. A real-time atmospheric delay correction model was established to consider both tropospheric and ionospheric delays. Six corner reflectors (CRs) were set up to ensure the accuracy of validation methods. Results showed that pixel location accuracies of up to 0.427 m standard deviation could be achieved. Furthermore, adjustment of the CRs can cause a marginal loss of ranging precision. After eliminating this error, the ranging accuracy was improved to 0.162 m. For YG-13, a single frequency GPS receiver is used and the orbital accuracy is the biggest factor restricting its slant-range accuracy. Results show that the YG-13 slant-range can achieve decimetre-level accuracy. YG-13 provides convenience in terms of access to control points and target locations that does not depend on ground equipment.

This study proposes an algebraic distributed source localisation algorithm that combines time difference of arrival (TDOA) and angle of arrival (AOA) measurements. The proposed algorithm uses AOAs to remove the unknown parameters in TDOA equations caused by the specially distributed structure. Then, the observation equations are transformed into a set of pseudo-linear equations and apply linear weighted least square to obtain the source position. The application of weighting matrix can lead to an approximate maximum likelihood estimator and produce a substantial improvement in source localisation accuracy. Both theoretical analysis and simulation results indicate the efficiency of the proposed algorithm and its performance can achieve the Cramer–Rao lower bound at a moderate noise level.

To solve the problem of mutual superposition and interference of multi-target micro-Doppler in midcourse, a method based on modified ant colony optimisation (ACO) is proposed. On the basis of building 3D time–frequency map, pheromone on each spot in the workspace can be updated, according to the changing rule of micro-Doppler. The pheromone leads ant to seek for required optimal micro-Doppler path gradually; thus single micro-Doppler curve corresponding to each scattering point can be separated. Simulation results indicate that the proposed method can overcome the coupling between micro-Doppler of different scattering point and the influence of background noise better, and implement effective separation of multi-target.

Space-time adaptive processing (STAP) for airborne radar with co-prime arrays is shown to have excellent superiority compared to traditional STAP with uniform linear array radar. However, high arithmetic computational complexity and large amount of training data are required in this approach. This motivates the authors to present a new approach which is relatively low computational load and fast convergence with satisfactory performance. Specifically, a reduced-dimension transformation in Doppler domain is incorporated into the existing approach. The reduced-dimension interference covariance matrix and target steering vector are then achieved by performing the reduced-dimension process, and hence two reduced-dimension STAP filters are designed using the derived interference covariance matrix and target-steering vector. Numerical simulations are carried out to reveal the superiority of the proposed approach.