Precipitable water vapour (PWV) is an important input for numerical weather prediction model, meteorology and high-precision navigational applications. Conventional methods for the determination of PWV using radiosonde are not sufficient owing to poor temporal resolution, whereas radiometer-derived PWV is reliable only in fair weather conditions. Global positioning system (GPS) is a very useful and cost-effective tool to determine PWV continuously in all weather conditions. The processing of GPS data to extract the PWV information is, however, very complicated due to very small effect of the PWV (∼0.5% of total delay) on GPS frequencies than other sources of delay and errors and requires a network of GPS in differential configuration for such purpose. The authors show how the problem can be handled in a standalone dual-frequency GPS receiver in a relatively less complicated manner with reasonable accuracy. The performances of different dry tropospheric delay models are also investigated. The methodology is tested with GPS measurements at Kolkata (22.57°N, 88.37°E) and Bangalore (13.01°N, 77.5°E). The results indicate that the proposed methodology can be implemented for PWV estimation using single GPS receiver with satisfactory performance.

In this study, an existing iterative least-squares (LS) method for determining ocean surface currents from X-band nautical radar images is modified for extracting ocean wave information from the same data. Within each iterative step, the image spectra samples are classified as containing contributions from fundamental, first-order and higher harmonic waves or noise. Based on the classification result, a new scheme is proposed to increase the robustness of current estimation. This involves automatically adjusting the first threshold that is used for obtaining an initial guess of the current velocity in the iterative LS method. The proposed wave algorithm directly uses the classified fundamental and first-order harmonic wave components for wave spectra and parameter retrieval. Unlike previous wave analysis techniques in which a bandpass filter is required to eliminate the non-wave contributions after the current velocity is obtained, the proposed algorithm simplifies the wave retrieval without such a bandpass filter. Algorithm verification is first conducted by using simulated radar images. Subsequently, the method is applied to field radar data and the results are compared with wave-buoy measurements. Wave parameters from both types of data show that the modified wave algorithm produces results that are close to those achieved using traditional algorithms.

This paper first introduces an accurate inverse synthetic aperture radar echo model for the fast moving targets. In this model, the target's motion during the time periods of the pulse transmitting, propagating and receiving have been taken into account, and some problems, which have been ignored in the ‘stop–go’ model, may occur, for example, the varied ambiguity numbers and the drifted frequency centre. These problems will cause many difficulties in obtaining a high resolution range profile (HRRP) synthesis. To deal with these problems, a stepped frequency synthetic preprocessing (SFSP) algorithm is presented. The key of the proposed algorithm is synthetic preprocessing, including Doppler ambiguity suppression, echo coherence restoration and frequency centre correction, respectively. By completing the preprocessing, the HRRP can be achieved by a bandwidth synthesis and a well-focused image can be obtained by a keystone transform and an azimuth process, respectively. The simulation results validate the proposed SFSP algorithm by comparing it with the algorithm in the existing extended ‘stop–go’ model.

Circular synthetic aperture radar (SAR) imaging on the geosynchronous orbit has many potential advantages, such as high-resolution three-dimensional (3D) imaging and continuous surveillance of broad area. The mission considered is an L-band geosynchronous circular SAR (GEOCSAR) with full aperture measurement. Since the integration time of GEOCSAR can be as long as 24 h, the orbit altitude is about 36 000 km and the coverage may reach 1/3 of the Earth's surface. The spatial and temporal variation of the ionosphere may impose significant effects on 3D imaging performance of GEOCSAR. The effects of ionospheric spatial variation including vertical and horizontal structure, the ionospheric turbulence and the ionospheric temporal variation are discussed. The analysis shows that the temporal variation of the ionospheric electron content during the synthetic aperture and the ionospheric turbulence may severely affect the GEOCSAR focusing performance on the XY plane. The vertical and horizontal structure of the ionosphere will cause image shift, and the dispersion effect is negligible.

The problem of multiple incident signals’ direction of arrival (DOA) estimation for spatially separated polarisation sensitive array (SS-PSA) is studied. The proposed SS-PSA is a sparse uniform array with orthogonally oriented and spatially separated dipole-triads. The proposed array can reduce the array mutual coupling by using the spatially separated polarised antenna instead of conventional spatially collocated polarised antenna. Moreover, the DOA estimation accuracy can be improved greatly due to the extended aperture offered by sparse array. Computer simulation results verify the effectiveness of the proposed algorithm.

In the context of unknown inputs (unknown dynamic biases) and unknown measurement systematic errors, this article studies the extension of robust three-stage Kalman filter (ERThSKF) that satisfies high precision entry navigation filter requirements for Mars pinpoint landing mission. The imprecise dynamic model with uncertain parameters could produce unknown inputs. Using radiometric beacons and/or inertial measurement unit (IMU) as output observation during the Mars atmospheric entry phase, the measurement data from the radio range and/or IMU have unknown measurement systematic errors. To solve these problems, we made an ERThSKF to obtain the accurate state estimation of the uncertain non-linear Mars system with unknown inputs and unknown measurement systematic errors which can be effectively estimated and compensated. Computer simulations show that the proposed navigation filter algorithm in this study can achieve high convergence speed and minor errors, which fulfils the need of future pinpoint Mars landing missions.

The radio hologram signal (RHS) extraction is the pre-condition of shadow inverse synthetic aperture radar (SISAR) imaging in forward scatter radar (FSR). However, for a ground-based FSR imaging system, which usually includes an envelope detection module, it is pretty hard to obtain the complex RHS. Thus a novel method for RHS reconstruction is proposed by considering the relationship between the in-phase part and the orthogonal part. The operation of envelope detection is never combined with segmented Hilbert transform before in RHS reconstruction and detailed skills in applying the method are discussed with simulations. Then, the proposed method is verified through real experimental data processing, of which a metal board and a microbus are regarded as the targets. Furthermore, target profiles via SISAR imaging processing are achieved very well when using the reconstructed RHS.

This study simulated the broadening first-order sea clutter spectrum and analysed the influence of ionosphere and bistatic angle on sea clutter spectrum for high-frequency (HF) hybrid sky-surface wave radar based on the mechanism of sea clutter broadening. Firstly, according to the propagation characteristics of HF waves in the ionosphere and the mechanism of the ionosphere contamination, a method of dynamic ionospheric phase contamination simulation is introduced. Secondly, the formula of the Bragg frequency of first-order sea clutter is presented derived from the system configuration, and a simulation method of broadening sea clutter is given. The influence of bistatic angle and different ionosphere state on the first-order sea clutter spectrum is further analysed. Finally, the results of theoretic analysis are examined with the experimental results based on the newly developed integrated HF sky-surface wave radar experimental system, and the dominant factor of sea clutter broadening is studied. Simulation results show that the results of experiment consist with that of theoretic analysis, simulated broadening sea clutter can better describe the characteristics of measured sea clutter.

Distributed analysis of target kinematics captured by a large network of sensors has received significant attention lately. Tracking moving targets in nonlinear systems is one of the most fundamental tasks in this regard and information-type consensus filters (ICFs) have been applied to this problem. To improve the estimate performance, a squared-root cubature information filter which can avoid numerically sensitive matrix operations such as matrix square-rooting and inversion has been developed firstly. And then, based on this filter, a decentralised information filtering algorithm is proposed in an improved consensus framework. Specifically, consensus update at each time-cycle in the modified consensus scheme is computed in two steps, first towards the predicted value and then towards the final information estimate update, which can improve average estimation accuracy and speed the average consensus. Besides the basic merits of the traditional ICFs, the resulting algorithm is more scalable and robust. Simulation results clearly show the advantage of the proposed algorithm compared with existing ICFs in the considered application scenario.

When multiple targets are within the same radar antenna beam and cannot be separated in the range dimension, the conventional imaging methods cannot be directly used to obtain a focused radar image. In this study, a new joint estimation algorithm for multi-targets’ motion parameters is proposed. In this method, the first-order Keystone transform is first applied to correct the range walk of multiple targets simultaneously, and then the Lv's transform is used to estimate the motion parameters of targets including velocity and acceleration. The signal-to-noise ratio threshold for the proposed method is also given. The proposed method is fast and can obtain the accurate parameter estimation without knowing the number of targets and their motion information. Experimental results demonstrate the performance of the proposed algorithm. Comparisons between the proposed method and other methods, the maximum-likelihood method, fractional Fourier transform and discrete polynomial transform, are performed, which show that the proposed method can efficiently obtain the accurate parameter estimation with low computational burden.

The precise disposal of azimuth variance of range cell migrations and motion errors in the one-stationary bistatic very high frequency/ultrahigh frequency ultra-wideband synthetic aperture radar imaging is a real challenge for efficient frequency-domain algorithms, but can be precisely managed by time-domain approaches. In this study, a novel bistatic fast factorised backprojection (BFFBP) algorithm is presented, which can deal with these two effects accurately and achieve the computational performance in parity with frequency-domain algorithms. First, the imaging geometry with arbitrary motion in elliptical polar coordinate is provided, and the analytical expression of the bistatic backprojection algorithm in this coordinate system is derived, which provides a theory basis for the proposed algorithm. Then, based on the subaperture imaging geometry, the sampling requirements considering motion errors is deduced, which offers the optimal tradeoff between the imaging quality and computational speed. The advantage of using elliptical polar coordinate system for implementing the BFFBP algorithm is analysed. Finally, the implementation and computational burden of the BFFBP algorithm are discussed. Simulation results are shown to prove the correctness of the theory analysis and validity of the proposed approach.

In this study, the authors propose an unsupervised terrain and land-use classification algorithm for polarimetric synthetic aperture radar (SAR) image analysis. Under the non-reflection symmetry condition, the non-negative eigenvalue decomposition (NNED) employing Arii volume scattering model is derived. They first apply NNED to divide pixels into three categories of surface, volume and double bounce scatterings. Then the pixels in each category are further divided into several classes based on the scattering characteristic parameter of the dominant scattering component. Utilising the initial classification result as training sets, the complex Wishart classifier can then be performed within each category or beyond categories to refine the final classification result. The effectiveness of this algorithm is demonstrated using the German Aerospace Center's E-SAR polarimetric data acquired over the Oberpfaffenhofen area in Germany.

Radar cross section (RCS) of a wind turbine has a key role for determining possible effects of wind farms on radar and navigation systems. Closed form expressions of the physical optics technique are applied to calculate monostatic radar cross section of an electrically large wind turbine model over a dielectric, lossy half space. The model is constructed with perfectly conducting canonical structures. First-order effects of the half space to the electromagnetic scattering mechanism are approximated with four-path model. Doppler spectrogram of the turbine model over lossy ground is obtained using short-time Fourier transform. The closed form expressions provide very-fast RCS calculations for different broadside directions and blade rotation speeds. Performance of this proposed method shows that it is suitable for real-time simulations that analyse the effects of the wind farms to the radar and navigation systems performance.

This study presents an improved scattered wave jamming method for synthetic aperture radar (SAR). The jammer adjusts the time-delay and the phase of the intercepted SAR signal. Then, a false scene is created to provide an effective protection for a certain area. It requires a lower jamming power than barrage jamming and has less computational complexity than direct-path deception jamming. Based on the performance analysis of scattered wave jamming, pulse repetition intervals to delay retransmission, and a modulation centre shift are proposed as improvements to enlarge the jamming area.

In this study, a generalised systematic bias (SB) is presented, which is represented via a dynamic model driven by structured unknown inputs (UI). The online SB estimation is implemented in two steps. In the first step, the state-free SB measurement and the UI-free SB dynamic model are derived in the case that UI-free condition holds. In the second step, the linear minimum mean squared filter is obtained via orthogonal principle, and the sufficient condition of filtering stability is presented. A simulation about target tracking is given to verify the proposed method.