IET Radar, Sonar & Navigation
Volume 12, Issue 1, January 2018
Volumes & issues:
Volume 12, Issue 1
January 2018
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- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 1, p. 1 –2
- DOI: 10.1049/iet-rsn.2017.0556
- Type: Article
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RSN Editorial 2018
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- Author(s): Changzheng Ma ; Tat Soon Yeo ; Boon Poh Ng
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 1, p. 3 –10
- DOI: 10.1049/iet-rsn.2017.0149
- Type: Article
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Multiple input multiple output (MIMO) radar forms large virtual aperture and improves the cross-range resolution of radar imaging. Sparse signal recovery algorithms can be used to improve image quality of target with sparse property in spatial domain. Conventional sparse signal recovery-based MIMO radar imaging method rearranges the received two-dimensional (2D) or 3D signals into a vector, then linear equations describing the relation between the received signal and the reflectivity of the scatterers are solved. However, this method occupies huge memory spaces and increases the computational load. In this study, by introducing synthetic codes, multidimensional linear equations of MIMO radar imaging are derived, which occupy less memory spaces and cost less computationally. A L1 L0 norms homotopy sparse signal recovery algorithm for multidimensional linear equations is used to recover the image. Simulation results verify the high efficiency of using multidimensional linear equations.
- Author(s): Xiaowen Zhang ; Kaizhi Wang ; Xingzhao Liu
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 1, p. 11 –20
- DOI: 10.1049/iet-rsn.2017.0107
- Type: Article
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In this study, the authors consider the problem of joint transmit waveform and receive filter design for cognitive radar. The problem is analysed in signal-dependent interference, as well as additive channel noise for an extended target with unknown target impulse response (TIR). To address this problem, an iterative algorithm is employed for target detection by maximising the average signal-to-interference-plus-noise ratio of the received echo on the premise of ensuring the TIR estimation precision. In this method, the transmit waveform and receive filter are optimally determined at each step based on the previous step. In particular, under the same constraint on waveform energy and bandwidth, the Lagrange multiplier method is also considered. Simulation results demonstrate that the proposed iterative algorithm waveform achieves a higher rate of performance significantly compared to Lagrange multiplier algorithm waveform and traditional linear frequency modulated waveform, in terms of estimation accuracy and detection performance.
- Author(s): Ali Noroozi and Mohammad Ali Sebt
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 1, p. 21 –29
- DOI: 10.1049/iet-rsn.2017.0117
- Type: Article
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The problem of estimating the location of a single target from time difference of arrival (TDOA) and angle of arrival (AOA) measurements using multi-transmitter multi-receiver passive radar system with widely separated antennas is discussed. A closed-form two-step target position estimator is presented and analysed. Using the measured AOAs, the method is able to resolve the weakness of the TDOA-based methods in estimating the target height. Several weighted least-squares minimisations are employed by the method to produce a location estimate. A weighting matrix in each step is employed to provide a significant improvement in the performance of the algorithm. The Cramer–Rao lower bound (CRLB) for target localisation accuracy is also developed. The proposed estimator is analytically shown to reach the CRLB for Gaussian TDOA and AOA noises at moderate noise level. Simulation studies indicate that the proposed hybrid TDOA/AOA location scheme performs better than any of the other algorithms, especially in the z-direction.
- Author(s): Rakesh Sharma and Rajib Kumar Panigrahi
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 1, p. 30 –36
- DOI: 10.1049/iet-rsn.2017.0241
- Type: Article
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The non-local means filters are popular and effective in speckle filtering as well as preservation of subtle details but have certain limitations. The limitation of NLM filter is its biased estimation in case of excessive speckle noise. Also, the similarity measure which preserves polarimetric or scattering property of data is the matter of interest in recent works. In this paper, a speckle filtering technique is presented which apart from reducing speckle noise, preserves polarimetric property, fine structures of the polarimetric SAR data and leads to an unbiased estimation in excessive noise. The filtering method adjusts weights iteratively, such that norm of distances is minimized. The proposed method is validated over two real PolSAR datasets (captured over San Fransisco Bay, USA & Mumbai coastal area, India by RADARSAT-2) and a synthesized SAR image. The qualitative and quantitative performance analysis is presented for the proposed method in terms of visual appearance of span, RGB PolSAR images, ENL and B-index. The proposed method is also evaluated for PSNR and SSIM on synthesized SAR image. It is found that the proposed method performs better than NLM filter and can be considered as a good alternative to NLM filters.
- Author(s): Eric W. Gill ; Yue Ma ; Weimin Huang
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 1, p. 37 –45
- DOI: 10.1049/iet-rsn.2017.0220
- Type: Article
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A method for mitigating antenna motion effects in high-frequency radar Doppler spectra developed from ocean backscatter is proposed. On the basis of the established radar cross-section models for a fixed antenna and for an antenna on a floating platform, the relationship between these models is examined. Through this relationship, motion compensation can be achieved by deconvolving the radar cross-section data with the derived transfer function. Four different deconvolution methods are illustrated and discussed in this study. Calculations involving a radar cross-section model, incorporating external noise, for an antenna on a floating platform are conducted in order to simulate field data and to examine this motion compensation method. The external noise is characterised as a white Gaussian zero-mean process. By using this newly developed radar cross-section model with external noise, motion compensation results under different sea states are examined. The outcomes indicate that an iterative Tikhonov regularisation deconvolution technique is superior to the other compensation methods implemented in this study.
- Author(s): Belal Al-Qudsi ; Niko Joram ; Mohammed El-Shennawy ; Frank Ellinger
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 1, p. 46 –55
- DOI: 10.1049/iet-rsn.2017.0285
- Type: Article
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This study presents a multi-band scalable positioning system that not only provides accurate means of navigation but also seamlessly extends the maximum number of reference and mobile nodes. Time synchronisation is carried out wirelessly, hence minimising the required hardware to easily set up the system. Due to its high precision and immunity to radio frequency interferences, a multi-band frequency modulated continuous wave (FMCW) radar system is designed particularly to handle the core time measurements. Large parts of the radar front-end are fully integrated in an application-specific integrated circuit. Furthermore, in order to withstand the complex indoor conditions, the system engages a particle filter based tracking algorithm as a data fusion platform. The measurements were evaluated in several practical conditions and compared with the state-of-the-art techniques. The evaluation scenarios include areas with line-of-sight and non-line-of-sight conditions. A root mean square positioning error of <17 and 31 cm was achieved in a coverage area of around 500 m2, in both outdoor and indoor conditions, respectively. To the best of the authors’ knowledge, the proposed system outperforms the current commercial systems not only in the aspect of positioning error, but also in the coverage efficiency.
- Author(s): Chao Zhou ; Quanhua Liu ; Xinliang Chen
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 1, p. 56 –63
- DOI: 10.1049/iet-rsn.2017.0114
- Type: Article
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By partial interception and multiple forwarding of a radar transmitting signal, digital radio frequency memory-based interrupted sampling repeater jamming can yield a partial processing gain and form multiple false target groups in the range direction, achieving jamming effects of both suppression and deception. Various improved jamming strategies have been proposed, while jamming suppression problems have not been fully addressed. In this study, a jamming suppression method based on the idea of ‘reconstruction and cancellation’ is proposed by analysing the jamming principle. The method firstly analyses the pulse compression results with time-frequency analysis to obtain the intercepted slice number and forwarding times; then, the slice width is estimated by deconvolution processing; finally, iterative cancellation is used to suppress the jamming. Performance of the method was verified by Monte Carlo simulation. The results show that the normalised error of the slice width estimation is <5% when the jamming-to-noise ratio reaches 15 dB (after pulse compress); the cancellation method can effectively restrain the jamming by bringing an improvement of signal-to-jamming ratio >16 dB.
- Author(s): Stephen Searle
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 1, p. 64 –73
- DOI: 10.1049/iet-rsn.2017.0046
- Type: Article
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Passive sensing involves the exploitation of ambient radio-frequency transmissions to infer the presence and properties of reflectors in the vicinity. With multiple receivers the directions of arrival (DOA) may be estimated. Interferometry is a simple means of DOA estimation, requiring minimal computational cost and as few as two receivers. However, interferometry suffers from ambiguity: signals incident from several distinct DOAs are indistinguishable because they yield the same measurement. This study considers interferometrical DOA estimation applied to the vehicular communications environment, assuming a vehicle equipped with two receivers. An algorithm for the disambiguation of DOA estimates using measurements from a second baseline is presented and a probabilistic analysis of this method is undertaken. The construction of extra baselines by consideration of the vehicle motion between signal frames is considered. The use of second-order measurement ratios generates baselines of acceptable length, given typical vehicle speeds. The effect of bias induced by second-order methods is explored.
- Author(s): Wenwu Kang ; Yunhua Zhang ; Xiao Dong
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 1, p. 74 –81
- DOI: 10.1049/iet-rsn.2017.0104
- Type: Article
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Micro-Doppler (m-D) effect is caused by vibrations and/or rotations of mechanical components of moving targets. The m-D signatures corresponding to such micro-motions (m-Ms) may significantly degrade the usefulness of synthetic aperture radar/inverse synthetic aperture radar (ISAR) imagery. The strong echo of the main body of a target can make the m-D parameter estimation of the vibrating or rotating parts more difficult. The removal of m-D effect from target's ISAR image is thus very important for realising high-resolution imaging of a complex target involving m-M parts. To treat this problem, the bivariate variational mode decomposition (BVMD) is proposed to get rid of the m-D effect from the image of target's main body. The BVMD method first decomposes the radar echoes of range cells into a series of complex-valued mode functions according to which m-D signatures can be distinguished and removed from common Doppler responses. Finally, a refined ISAR image of the main body is produced using conventional range–Doppler imaging algorithms. Both simulated and real measured data are processed to show the effectiveness of the proposed method.
- Author(s): Xingyu He ; Ningning Tong ; Xiaowei Hu ; Weike Feng
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 1, p. 82 –86
- DOI: 10.1049/iet-rsn.2017.0161
- Type: Article
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Owing to the sparsity of the space distribution of point scatterers, compressed sensing (CS) method is successfully applied in inverse synthetic aperture radar (ISAR) imaging. However, in addition to sparsity, ISAR images usually exhibit group sparse structure. Here, the authors propose a novel two-dimensional (2D) group primal dual active set with continuation (2DGPDASC) algorithm to recover an ISAR image, which always exhibit 2D group sparse structure. This algorithm is based on the regularised least-squares problem with an penalty model. At each iteration of the proposed method, it involves solving a least-squares problem on the active set only, and exhibits a fast local convergence within a finite step. Experimental results validate the effectiveness and superiority of the proposed method.
- Author(s): Dehua Zhao ; Yinsheng Wei ; Yongtan Liu
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 1, p. 87 –94
- DOI: 10.1049/iet-rsn.2017.0232
- Type: Article
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By properly transmitting pulses through the clear frequency bands, the hopped-frequency (HopF) waveform can achieve a large synthetic bandwidth while avoiding the complexity of wideband hardware as well as the mutual interference to/from adjacent RF users. To optimally design the HopF waveform with low range sidelobes under given spectral constraints, we propose a two-step-based approach in this paper. In the first step, a deterministic approach is presented to produce a rough approximation of the optimum solution to address the non-convexity of the waveform design. In the second step, gradient method is applied to locally refine the solution obtained in the first step. The proposed design method is efficient as the main computation in the first step lies in solving a convex optimisation which can be achieved in polynomial time and the iterative operations in the second step can be implemented using non-uniform fast Fourier transform. Experimental evidence suggests that the proposed method can produce near optimal solution in remarkably little time.
- Author(s): Liang Yu ; Yongmei Cheng ; Song Li ; Huisheng Zhao ; Zhunga Liu
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 1, p. 95 –103
- DOI: 10.1049/iet-rsn.2017.0298
- Type: Article
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During the torpedo guidance procedure, homing-torpedo beam allocation and guidance operate in a fixed allocation mode. However, in the complicated acoustic-warfare environment, the true target is very likely to release many decoys. The torpedo must constantly detect and track multiple targets at the same time before the actual target is confirmed. Based on the analysis of the environment, this study suggests an efficacy-computation model on the basis of lobes and a secondary beam-disposal framework based on beam formation and beam allocation, in addition to the universal norm for lobe classification based on the maximum efficacy. Based on considering four factors simultaneously – target probability, tracking demand, identification needs and task requirements – a comprehensive self-adaptive beam-allocation method is proposed. First, the whole beam section is divided into many lobes based on all target positions, and then all the target efficacies in each lobe can be computed. The calculation methods for both the efficacy function of each factor and the overall efficacy function are also provided. The simulation results show that this method can ensure that the stable tracking of multiple targets and the goals is identified simultaneously. This method can provide a rational and effective approach to multiple-target beam allocation.
- Author(s): Yaqi Deng ; Jun Wang ; Jue Wang ; Xiaoyong Lyv
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 1, p. 104 –111
- DOI: 10.1049/iet-rsn.2017.0152
- Type: Article
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In this study, a novel cascaded interference suppression method based on sparse representation (SR) is proposed for a passive airborne radar, which suffers from severe background interference due to the random range side-lobes coupling (RRSC) effect of the strong interference signals. The sparse nature of the RRSC covariance matrix is analysed and the SR is integrated into the proposed method accordingly, which reduces the computational complexity greatly without degrading the performance in interference suppression. Moreover, the proposed method is insensitive to the selection of the suppression order, which should be carefully selected in the traditional methods according to the prior information of the interference signals. A range of simulations have been conducted in the study to test the proposed method.
- Author(s): Huilong Zhang ; Benoite de Saporta ; Francois Dufour ; Dann Laneuville ; Adrien Nègre
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 1, p. 112 –120
- DOI: 10.1049/iet-rsn.2017.0123
- Type: Article
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The authors present in this study a numerical method which computes the optimal trajectory of a underwater vehicle subject to some mission objectives. The method is applied to a submarine whose goal is to best detect one or several targets, or/and to minimise its own detection range perceived by the other targets. The signal considered is acoustic propagation attenuation. This approach is based on dynamic programming of a finite horizon Markov decision process. A quantisation method is applied to fully discretise the problem and allows a numerically tractable solution. Different scenarios are considered. The authors suppose at first that the position and the velocity of the targets are known and in the second they suppose that they are unknown and estimated by a Kalman type filter in a context of passive tracking.
- Author(s): Yan Fu ; Xianrong Wan ; Xun Zhang ; Jianxin Yi ; Jian Zhang
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 1, p. 121 –129
- DOI: 10.1049/iet-rsn.2017.0106
- Type: Article
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The multipath clutter cancellation, the most computationally demanding part of signal processing in passive bistatic radar (PBR), is a key challenge in real-time processing. However, the previous extensive cancellation algorithm (ECA) versions have their limitations in parallel implementation. In this study, an advanced version of ECA is proposed for multipath clutter cancellation in passive radar. The proposed method can improve the computational efficiency via dividing the whole signal into more batches than ECA-batches and yielding an excellent cancellation performance at the same time. Simulation and experimental results following the theoretical analysis verify the performance of the new approach, which provides a valuable basis for real-time signal processing in PBR.
- Author(s): Yongsheng Zhao ; Yongjun Zhao ; Chuang Zhao
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 1, p. 130 –136
- DOI: 10.1049/iet-rsn.2017.0235
- Type: Article
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This study deals with the problem of joint delay–Doppler estimation in a practically motivated scenario of passive bistatic radar, where the surveillance channel is polluted by the direct-path signal residual. A new joint delay–Doppler maximum-likelihood estimator (MLE) based on Markov chain Monte Carlo (MCMC) is proposed. The MCMC method allows one to compute the MLE in a computationally efficient manner. The proposed estimator is based upon generating random variates using a Markov Chain whose stationary distribution approximates the likelihood function and guarantees convergence to the global maximum. In contrast to the recently proposed modified cross-correlation estimator, and the expectation–maximisation-based MLE, it avoids grid search which may lead to a straddle loss or initialisation-dependent iteration which may lead to convergence problems. Simulation results indicate that the proposed estimator achieves a significant performance improvement over existing methods.
- Author(s): Zhe Xiang ; Baixiao Chen ; Minglei Yang
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 1, p. 137 –144
- DOI: 10.1049/iet-rsn.2016.0648
- Type: Article
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Controlling the polarisation states of the transmitter and the receiver enables improving the performance of radar systems, especially for mainlobe interference suppression applications. In this study, the authors consider the design of optimal polarisations at both of the radar transmitter and receiver for mainlobe interference suppression. They propose the polarimetric multiple-input–multiple-output (MIMO) radar which combines the advantages of MIMO systems with the advantages offered by optimally choosing the transmitter polarisation or the receiver polarisation to achieve a better anti-jamming performance. The polarisation diversity is employed in the transmit array and the receive array. The interferences can be suppressed by the oblique projection filter. Based on the output signal-to-interference-plus-noise ratio analysis, the optimal transmitter polarisation and the receiver polarisation can be obtained. Simulation results demonstrate that interference can be effectively suppressed with the radar configuration, and better interference suppression performance can be achieved with the optimal transmitter polarisation and receiver polarisation.
Multiple input multiple output radar imaging based on multidimensional linear equations and sparse signal recovery
Joint optimisation of transmit waveform and receive filter for cognitive radar
Algebraic solution for three-dimensional TDOA/AOA localisation in multiple-input–multiple-output passive radar
Improved patch-based NLM PolSAR speckle filter based on iteratively re-weighted least squares method
Motion compensation for high-frequency surface wave radar on a floating platform
Scalable indoor positioning system with multi-band FMCW
Parameter estimation and suppression for DRFM-based interrupted sampling repeater jammer
Disambiguation of interferometric DOA estimates in vehicular passive radar
Micro-Doppler effect removal for ISAR imaging based on bivariate variational mode decomposition
High-resolution ISAR imaging based on two-dimensional group sparse recovery
Hopped-frequency waveform design for range sidelobe suppression in spectral congestion
Adaptive beam-allocation method based on lobe efficacy
Cascaded interference suppression method based on sparse representation for airborne passive radar
Stochastic control of observer trajectories in passive tracking with acoustic signal propagation optimisation
Parallel processing algorithm for multipath clutter cancellation in passive radar
Joint delay–Doppler estimation for passive bistatic radar with direct-path interference using MCMC method
Transmitter/receiver polarisation optimisation based on oblique projection filtering for mainlobe interference suppression in polarimetric multiple-input–multiple-output radar
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- Author(s): Eun Hee Kim and Ki Hyun Kim
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 1, p. 145 –150
- DOI: 10.1049/iet-rsn.2017.0250
- Type: Article
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Using a maximum-likelihood (ML) estimator for high-resolution angle estimation is well-suited for automotive radars. It is superior to other estimators in cases of small antenna aperture, small samples, and correlated signals. However, the computing power it requires prevents its widespread implementation. In this study, the authors propose a novel implementation method of the ML estimator that achieves appropriate memory requirements and computational costs by defining new variables. The proposed method is appropriate for practical implementation because calculation of the objective function is based only on independent multiply–add operations and can be easily parallelised. Real measured data from their radar of an unmanned ground vehicle system demonstrates the performance of the proposed method. Experimental results show that the proposed ML estimator is more robust than the conventional MUltiple SIgnal Classification method under conditions of low signal-to-noise ratio and a small number of snapshots.
Efficient implementation of the ML estimator for high-resolution angle estimation in an unmanned ground vehicle
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