Showing papers on "Moving target indication published in 2015"
TL;DR: A novel framework of space-time adaptive processing (STAP) radar is established with FDA as the transmit array and the proposed secondary range dependence compensation (SRDC) method is proposed, demonstrating the superiority of the proposed approach in clutter suppression under range ambiguous clutter scenarios.
Abstract: Airborne radar arrays oriented toward any direction other than sidelooking cause the range dependence of clutter. It is difficult to handle this range dependence problem in the presence of range ambiguity. Frequency diverse array (FDA) employs a small frequency increment across the array elements, which induces the spatial frequency variant with respect to slant range. Thus, it provides extra degrees-of-freedom in range domain. In this paper, a novel framework of space-time adaptive processing (STAP) radar is established with FDA as the transmit array. In the FDA-STAP radar, the range ambiguous clutter can be discriminated in spatial frequency domain. This is due to the fact that the spatial frequencies of the clutters from different slant ranges are distinguishable even though the range ambiguous clutter is within the same range bin. Simultaneously, the FDA-STAP radar induces secondary range dependence of clutter. To alleviate the secondary range dependence of clutter, a secondary range dependence compensation (SRDC) method is proposed for two cases: 1) the target is assumed in the unambiguous range region and 2) the target is assumed in the ambiguous range region. After the range ambiguous clutter is separated in the spatial frequency domain by using the proposed SRDC method, the traditional clutter compensation approach is applied to further align the spectrum distribution of clutter. Our simulation results demonstrate the superiority of the proposed approach in clutter suppression under range ambiguous clutter scenarios.
135 citations
TL;DR: The two-step GMTI algorithm has the ability of indicating multiple moving targets, particularly those submerged by the clutter; the practical GMTIm algorithm shows a robust performance in real data moving target imaging since the motion errors are estimated and compensated.
Abstract: Detection and imaging of multiple moving targets is a challenging task, particularly with real synthetic aperture radar (SAR) data. In this paper, moving targets with different motion parameters are classified based on the relative locations of their spectra to that of the clutter. Based on the classification, a novel moving target processing strategy with real SAR data is proposed, including a two-step ground moving target indication (GMTI) algorithm and a practical ground moving target imaging (GMTIm) algorithm with motion error compensation. The two-step GMTI algorithm has the ability of indicating multiple moving targets, particularly those submerged by the clutter; the practical GMTIm algorithm shows a robust performance in real data moving target imaging since the motion errors are estimated and compensated. Both simulated and real data processing results are provided to demonstrate the effectiveness of the proposed strategy.
81 citations
TL;DR: Experiments with simulated and real radar data sets indicate that the proposed RLCAF can achieve higher integration gain and detection probability of a marine target in a low signal-to-clutter ratio environment.
Abstract: Robust and effective detection of a marine target is a challenging task due to the complex sea environment and target's motion. A long-time coherent integration technique is one of the most useful methods for the improvement of radar detection ability, whereas it would easily run into the across range unit (ARU) and Doppler frequency migration (DFM) effects resulting distributed energy in the time and frequency domain. In this paper, the micro-Doppler (m-D) signature of a marine target is employed for detection and modeled as a quadratic frequency-modulated signal. Furthermore, a novel long-time coherent integration method, i.e., Radon-linear canonical ambiguity function (RLCAF), is proposed to detect and estimate the m-D signal without the ARU and DFM effects. The observation values of a micromotion target are first extracted by searching along the moving trajectory. Then these values are carried out with the long-time instantaneous autocorrelation function for reduction of the signal order, and well matched and accumulated in the RLCAF domain using extra three degrees of freedom. It can be verified that the proposed RLCAF can be regarded as a generalization of the popular ambiguity function, fractional Fourier transform, fractional ambiguity function, and Radon-linear canonical transform. Experiments with simulated and real radar data sets indicate that the RLCAF can achieve higher integration gain and detection probability of a marine target in a low signal-to-clutter ratio environment.
76 citations
TL;DR: A signal processing strategy is proposed to track multiple extended targets in a scene by means of a wide-band monostatic through-wall radar and an extended target-tracking approach is applied to properly exploit at the tracking stage the information related to extended nature of targets.
Abstract: Tracking moving targets hidden behind visually opaque structures as building walls is a crucial issue in many surveillance, rescue, and security applications. The electromagnetic waves at the low microwave frequency range penetrate into common building materials and thereby enable the radar to expose behind the wall scene. However, due to complexity of the scattering scenario, the radar signal undergoes multipath propagation phenomena. These typically manifest themselves as environmental clutter which may impair detection and tracking of true targets. In this paper, a signal processing strategy is proposed to track multiple extended targets in a scene by means of a wide-band monostatic through-wall radar. The system collects data sets at regular time steps which are first processed by a microwave tomographic technique. Then, a detection/tracking stage is implemented in order to track the position and dynamics of targets in real time. An extended target-tracking approach is applied to properly exploit at the tracking stage the information related to extended nature of targets. The effectiveness of the proposed signal processing chain is assessed by numerical tests based on full-wave data pertaining to an indoor scenario.
70 citations
TL;DR: An efficient Radon transform (RT) estimation is proposed to estimate the radial velocity of fast moving target by utilizing the geometry information, and much more geometry information is exploited to realize clutter cancellation, noise cancellation, and estimation error minimizing in the RT domain, which is not proposed by the others.
Abstract: Real-time radial velocity estimation is a key challenge for moving target imaging and location in current single-antenna synthetic aperture radar (SAR)-ground moving target indication systems Since the conventional methods suffer from ambiguity, complexity realization, or heavy computation load for fast moving target motion estimation, this paper emphasizes the estimation efficiency by simple realization An efficient Radon transform (RT) estimation is proposed to estimate the radial velocity of fast moving target by utilizing the geometry information, and much more geometry information is exploited to realize clutter cancellation, noise cancellation, and estimation error minimizing in the RT domain, which is not proposed by the others With only two to four angles used to calculate rather than search for the radial velocity of moving targets, the proposed methods simplify the conventional range and angle (2-D) searching procedure into several time range (1-D) searching procedure efficiently The theoretical and experimental analysis provides qualitative and quantitative evaluations into the effectiveness of the proposed methods In the single-antenna SAR system, the proposed methods can estimate the radial velocity of fast moving target efficiently and accurately in high signal to clutter plus noise ratio scenarios
69 citations
TL;DR: Numerical results indicate that the proposed range training-free detector offers improved detection performance over covariance matrix based detectors when the latter are provided with a moderate amount of training signals.
Abstract: This paper examines moving target detection in distributed multi-input multi-output radar with sensors placed on moving platforms. Unlike previous works which were focused on stationary platforms, we consider explicitly the effects of platform motion, which exacerbate the location-induced clutter non-homogeneity inherent in such systems and thus make the problem significantly more challenging. Two new detectors are proposed. The first is a sparsity based detector which, by exploiting a sparse representation of the clutter in the Doppler domain, adaptively estimates from the test signal the clutter subspace, which is in general distinct for different transmit/receive pairs and, moreover, may spread over the entire Doppler bandwidth. The second is a fully adaptive parametric detector which employs a parametric autoregressive clutter model and offers joint model order selection, clutter estimation/mitigation, and target detection in an integrated and fully adaptive process. Both detectors are developed within the generalized likelihood ratio test (GLRT) framework, obviating the need for training signals that are indispensable for conventional detectors but are difficult to obtain in practice due to clutter non-homogeneity. Numerical results indicate that the proposed training-free detectors offer improved detection performance over covariance matrix based detectors when the latter have a moderate amount of training signals.
61 citations
TL;DR: The objective of the paper is to highlight the limitations and challenges to be considered when processing real, multichannel GMTI data from pioneering SAR sensors for maritime surveillance.
Abstract: This paper explores the ground moving target indication (GMTI) capabilities of the German Aerospace Center’s state-of-the-art airborne (F-SAR) and spaceborne (TerraSAR-X) synthetic aperture radars (SARs) when operating over maritime scenarios. The performance of classical dual channel GMTI techniques, such as displaced phase center antenna (DPCA) and along-track interferometry (ATI), as well as the promising adaptive techniques, like extended DPCA (EDPCA) and imaging space–time adaptive processing (ISTAP) have been analyzed on the basis of experimental acquisitions with both sensors. The objective of the paper is to highlight the limitations and challenges to be considered when processing real, multichannel GMTI data from pioneering SAR sensors for maritime surveillance. Different calibration or channel balancing strategies, on the basis of the digital balancing (DB) method, are studied, considering their impact on SAR-GMTI performance. An adaptive SAR processor, accounting for target kinematics and based on a matched filter bank (MFB) approach, is integrated in the SAR-GMTI processing chain in order to retrieve refocused images of the moving vessels.
53 citations
TL;DR: A special matched reconstruction filter bank (MRFB) is introduced and incorporated into two novel low PRF ground moving target indication (GMTI) algorithms, which can be performed simultaneously without the need of a separate high PRF system operation mode.
Abstract: In this paper, a novel method for enabling ground moving target capability for high-resolution wide-swath (HRWS) synthetic aperture radar (SAR) systems is presented. Such HRWS SAR systems are generally operated with very low pulse repetition frequencies (PRFs). With the novel method, moving target signals highly aliased in Doppler can be reconstructed and the targets’ motion parameters and actual positions can be estimated with high accuracy. A special matched reconstruction filter bank (MRFB) is introduced and incorporated into two novel low PRF ground moving target indication (GMTI) algorithms. Owing to the application of the MRFB, GMTI and HRWS SAR imaging can be performed simultaneously without the need of a separate high PRF system operation mode, which, so far, was necessary for achieving a reasonable GMTI performance. With the MRFB, the advantages of the HRWS imaging principle, i.e., the wide swath and the high resolution are preserved for both HRWS SAR imaging and GMTI. Potential applications are wide-area land and maritime traffic monitoring, where the benefit of the preserved high resolution could, for instance, be used for generating high-quality inverse SAR (ISAR) images for target recognition purposes.
51 citations
TL;DR: The proposed clutter suppression and imaging approach is not only adapted for uniformly displaced phase center sampling but also for the nonuniform sampling cases.
Abstract: This paper describes a clutter suppression approach and the corresponding moving target imaging algorithm for a multichannel in azimuth high-resolution and wide-swath (MC-HRWS) synthetic aperture radar (SAR) system. Incorporated with digital beamforming processing, MC-HRWS SAR systems are able to suppress the Doppler ambiguities to allow for HRWS SAR imaging and null the clutter directions to suppress clutter for ground moving target indication. In this paper, the degrees of freedom in azimuth for the multichannel SAR systems are employed to implement clutter suppression. First, the clutter and moving target echoes are transformed into the range compression and azimuth chirp Fourier transform frequency domain, i.e., coarse-focused images formation, when the clutter echoes are with azimuth Doppler ambiguity. Considering that moving targets are sparse in the imaging scene and that there is a difference between clutter and a moving target in the spatial domain, a series of spatial domain filters are constructed to extract moving target echoes. Then, using an extracted moving target echo, two groups of signals are formed, and slant-range velocity of a moving target can be estimated based on baseband Doppler centroid estimation algorithm and multilook cross-correlation Doppler centroid ambiguity number resolving approach. After the linear range cell migration correction and azimuth focus processing, a well-focused moving target image can be obtained. In addition, the proposed clutter suppression and imaging approach is not only adapted for uniformly displaced phase center sampling but also for the nonuniform sampling cases. Some simulation experiments are taken to demonstrate our proposed algorithms. Finally, some real measured data results are presented to validate the theoretical investigations and the proposed approaches.
49 citations
TL;DR: A new ground moving target imaging algorithm for airborne synthetic aperture radar (SAR) based on a novel time-frequency representation (TFR), Lv's distribution (LVD), which is capable of imaging multiple moving targets even when they are located at the same range resolution cell is presented.
Abstract: This paper presents a new ground moving target imaging (GMTIm) algorithm for airborne synthetic aperture radar (SAR) based on a novel time-frequency representation (TFR), Lv's distribution (LVD). We first analyze generic moving target signatures for a multichannel SAR and then derive the analytical spectrum of a point target moving at a constant velocity by a polar format algorithm for SAR image formation. SAR motion deviation from a predetermined flight track is considered to facilitate airborne SAR applications. LVD, as a recently developed TFR for the analysis of multicomponent linear-frequency-modulated signal, is adopted to represent the target kinematic spectrum in the Doppler centroid frequency and chirp rate domain. As a result, the proposed SAR-GMTIm algorithm is capable of imaging multiple moving targets even when they are located at the same range resolution cell. Some practical issues such as imaging maneuvering targets and small/weak targets are discussed to enhance the applicability of the proposed algorithm. Simulation results with isotropic point moving targets are presented to validate the effectiveness and superiority of the proposed algorithm. Raw data collected by an airborne multichannel SAR are also used to verify the performance improvement made by the proposed algorithm.
45 citations
TL;DR: A fast RPCA-based detection method for multichannel SAR under a strong clutter background even with channel unbalance or platform motion error is proposed and it can work cooperatively with the existing space-time adaptive processing method to get a more robust detection performance.
Abstract: Clutter suppression and ground moving target indication are challenging tasks in multichannel synthetic aperture radar (SAR) systems. In recent years, robust principal component analysis (RPCA) has attracted much attention for its good performance in distinguishing the different parts from a set of correlative database. Therefore, we propose a fast RPCA-based detection method for multichannel SAR under a strong clutter background in this letter even with channel unbalance or platform motion error. Subsequently, as the existing space-time adaptive processing (STAP) method would fail when the training samples are contaminated by the moving target, we apply the RPCA-based method in the range-Doppler domain to improve the performance of STAP. Since the regions of targets can be detected via RPCA, the remaining samples, which can be regarded as only clutter, are used to estimate the covariance matrix for further processing. The final experiments based on real measured data set show its good performance under the strong clutter background. Although the RPCA-based result differs from that of the STAP method, they can work cooperatively to get a more robust detection performance.
01 Nov 2015
TL;DR: Numerical results indicate that the proposed training-free detectors offer improved detection performance over covariance matrix based detectors when the latter have a moderate amount of training signals.
Abstract: This paper examines moving target detection (MTD) in distributed multi-input multi-output (MIMO) radar with sensors placed on moving platforms. Unlike previous works which were focused on the case of stationary platforms, we consider explicitly the effects of platform motion, which exacerbate the location-induced clutter non-homogeneity inherent in such systems and thus make the MTD problem significantly more challenging. We propose a sparsity based detector which, by exploiting a sparse representation of the clutter in the Doppler domain, adaptively estimates from the test signal the clutter subspace, which is allowed to be distinct for different transmit/receive (Tx/Rx) pairs and, moreover, may spread over the entire Doppler bandwidth. The proposed detector requires no range training signals that are indispensable for conventional detectors but are difficult to obtain in practice. Numerical results indicate that the proposed range training-free detector offers improved detection performance over covariance matrix based detectors when the latter are provided with a moderate amount of training signals.
TL;DR: Ground moving-target indication (GMTI) has been extensively used in the measuring of ocean surface currents and ground traffic and the influence of rebound jamming on synthetic aperture radar (SAR) GMTI is studied in this letter.
Abstract: Ground moving-target indication (GMTI) has been extensively used in the measuring of ocean surface currents and ground traffic. The influence of rebound jamming on synthetic aperture radar (SAR) GMTI is studied in this letter. The rebound jamming signal is either deceptive or barrage jamming according to the time delay. When the time delay between each pulse is constant, the jamming focused on a morphed image of the imaging area. After displaced phase-center antenna (DPCA) processing, the image with azimuth near the jammer's azimuth will be canceled similar to stationary targets, and the other part of the DPCA image remains. When the time delay is random between each pulse, the rebound jamming is barrage jamming for both the SAR image and the DPCA image. The validity of the proposed method is verified by theoretic analysis and simulation results.
TL;DR: A WCR waveform design method is proposed for target detection by maximizing the average signal to clutter plus noise ratio of the received echo on the premise of ensuring the TRS estimation precision and a fast hierarchical scheme is proposed with comparative performance.
Abstract: As the target radar signature (TRS) is target-radar orientation sensitive and time varying in wideband cognitive radar (WCR), the TRS information ofWCR should be recursively updated by the receiver on the fly. Therefore, in WCR waveform design for target detection, TRS estimation ability should also be considered to provide the prior knowledge for the optimization of the next waveform. To address this problem, a WCR waveform design method is proposed for target detection by maximizing the average signal to clutter plus noise ratio of the received echo on the premise of ensuring the TRS estimation precision. By constraining the estimation performance, a convex cost function is established and the optimal solution can be obtained by the existing convex programming algorithm. Furthermore, for the convenience of waveform optimization in real time, a fast hierarchical scheme is also proposed with comparative performance. Numerical results show that, the proposed methods are able to improve the target detection performance under given estimation performance constraint.
TL;DR: This paper proposes a new optimized multichannel synthetic aperture radar configuration, based on receiving antennas with nonuniformly displaced phase centers, intended for ground moving target indication (GMTI) applications over maritime scenarios, compared with current SAR missions.
Abstract: This paper proposes a new optimized multichannel synthetic aperture radar (SAR) configuration, based on receiving antennas with nonuniformly displaced phase centers, intended for ground moving target indication (GMTI) applications over maritime scenarios. This system is compared with current SAR missions, such as TerraSAR-X (TSX) or TanDEM-X (TDX). The GMTI capabilities of the different configurations are analyzed in a two-level performance approach. First, an intensive numerical simulation evaluation, based on Monte Carlo trials, is carried out in order to characterize the probabilities of detection under different system parameters and scenario conditions. Different GMTI techniques, i.e., displaced phase center antenna, along-track interferometry, and extended displaced phase center antenna, are assessed. In a second step, synthetic simulated SAR data, obtained in a study case scenario, is used to demonstrate the potential improvement of the proposed multichannel configuration compared with current SAR missions, providing subclutter visibility for maritime surveillance of small and slowly moving boats.
TL;DR: In this article, a performance analysis of ground moving targets detection by means of interferometric synthetic aperture radar (ATI-SAR) systems and using a statistical approach is carried out on both simulated and real data.
Abstract: The availability of high-resolution along-track interferometric synthetic aperture radar (ATI-SAR) data with large coverage, such as TerraSAR-X (TSX) data, motivates spaceborne ground moving target detection as an attractive alternative to conventional traffic data acquisition. In this paper, a performance analysis of ground moving targets detection by means of ATI-SAR systems and using a statistical approach is carried out on both simulated and real data. A Gaussian clutter model and a deterministic target response have been assumed. The receiver operating characteristic for the likelihood ratio test (LRT), which can be assumed as a reference best performance case, has been expressed in closed form and has been related to the deflection values, which can be exploited for assessing the improvements in the detection probability with a constant false-alarm rate. For practical applications, the performance of a generalized LRT (GLRT) has been investigated. The analysis carried out on simulated data revealed that the detection results achieved using a GLRT based on a deterministic target model are comparable with those obtained using a GLRT based on a Gaussian target model and are not significantly worse than the theoretical performance of the LRT. Finally, ground moving target detection results on TSX real data are showed.
TL;DR: Simulation results demonstrate that the proposed detector outperforms several existing detectors, particularly in the capacity to handle extremely heterogeneous environments, as well as a new test, called the Degree of Radial-Velocity Consistency (DRVC) test.
Abstract: This paper deals with target-detection issues in extremely heterogeneous environments, with a multichannel synthetic-aperture-radar-based ground moving-target indication (SAR-GMTI) system, and proposes a new detector with the aim of addressing such extremely heterogeneous environments The proposed detector is a multistage one: The first detection stage implements the conventional Displaced Phase Center Array test, but the second stage implements a new test, which is called the Degree of Radial-Velocity Consistency (DRVC) test We will show that the newly developed DRVC test possesses two pronounced characteristics The first characteristic is that the DRVC test incorporates such a priori knowledge that the radial velocities corresponding to the individual components of a moving target are all equal, while the second characteristic of the DRVC test is its clutter-heterogeneity-independent property The two characteristics make the proposed detector a good candidate for addressing extremely heterogeneous environments Simulation results demonstrate that the proposed detector outperforms several existing detectors, particularly in the capacity to handle extremely heterogeneous environments Moreover, the application of the proposed detector to a set of real-measured three-channel airborne SAR-GMTI data further demonstrates the efficacy of the proposed detector
10 May 2015
TL;DR: A new approach for detecting a particular class of moving targets that exploits characteristics of specific non-linear targets to both eliminate moving objects that are not of interest and suppress stationary clutter is presented.
Abstract: A new approach for detecting a particular class of moving targets is presented. This method exploits characteristics of specific non-linear targets to both eliminate moving objects that are not of interest and suppress stationary clutter. Details of the underlying physical phenomena are discussed, and the signal processing procedures leveraged by the non-linear radar system are outlined in detail.
TL;DR: An improved track initiation algorithm based on a heading-parameterized multiple model (HPMM) method that uses the sign of the range-rate measurement, prior knowledge of target maximum speed, and MDV to reduce the bias in the initial velocity estimate.
Abstract: A ground moving target indicator (GMTI) radar measures range, azimuth, and Doppler or range-rate of a target. The range-rate measurement, which is the key measurement of a GMTI radar, is used to differentiate a ground moving target from clutter when the radial velocity of the target exceeds the minimum detectable velocity (MDV). The range and azimuth measurements provide an accurate estimate of the target position. A number of track initiation algorithms using GMTI measurements are known at present. All track initiation algorithms set the initial velocity to zero and a large prior covariance for velocity is used based on the maximum target speed. The range-rate measurement is then used to update the target velocity or state. The range-rate measurement contains only the component of the target velocity along the radar line-of-sight (RLOS) and no component of velocity in the perpendicular direction is measured. As a result, existing track initiation algorithms produce a bias in the velocity estimate. This paper first corrects two errors in the single-point (SP) track initialization part of the paper [29] using the range-rate measurement to obtain the initial velocity estimate and associated covariance. Secondly, we present an improved track initiation algorithm based on a heading-parameterized multiple model (HPMM) method that uses the sign of the range-rate measurement, prior knowledge of target maximum speed, and MDV. The proposed algorithm reduces the bias in the initial velocity estimate and the superior performance of the algorithm is demonstrated using Monte Carlo simulations.
TL;DR: This paper demonstrates for the first time successful GMTI from a space-based SAR employing two parallel receive channels in the flight direction that operates in a scanSAR mode.
Abstract: This paper demonstrates for the first time successful GMTI from a space-based SAR employing two parallel receive channels in the flight direction that operates in a scanSAR mode. ScanSAR in conjuction with GMTI offers wide-area monitoring of moving objects, an important prerequisite for many applications, for instance, maritime domain awareness. The multichannel capability to suppress background clutter permits improved detectability in challenging environments, such as vessel detection in near range or high sea states, and additionally offers the possibility to estimate target speeds and headings.
17 Jun 2015
TL;DR: A new method for mitigating wall return and a new greedy algorithm for detecting stationary targets after wall clutter has been cancelled are presented, which improves upon the target detection sensitivity of a Fourier-based technique.
Abstract: We present a new method for mitigating wall return and a new greedy algorithm for detecting stationary targets after wall clutter has been cancelled. Given limited measurements of a stepped-frequency radar signal consisting of both wall and target return, our objective is to detect and localize the potential targets. Modulated Discrete Prolate Spheroidal Sequences (DPSS's) form an efficient basis for sampled bandpass signals. We mitigate the wall clutter efficiently within the compressive measurements through the use of a bandpass modulated DPSS basis. Then, in each step of an iterative algorithm for detecting the target positions, we use a modulated DPSS basis to cancel nearly all of the target return corresponding to previously selected targets. With this basis, we improve upon the target detection sensitivity of a Fourier-based technique.
TL;DR: A sea clutter mitigation method based on sparse optimization is proposed and tested with real radar data collected using a 2.425-GHz netted radar system and it is shown that the extracted signal had a lower false alarm rate compared to the original signal.
Abstract: A sea clutter mitigation method based on sparse optimization is proposed and tested with real radar data collected using a 2.425-GHz netted radar system developed at University College London, London, U.K. The proposed method was able to separate the target returns from the sea clutter returns, thus increasing the signal-to-interference ratio. It is shown that the extracted signal had a lower false alarm rate compared to the original signal.
10 May 2015
TL;DR: A new airborne radar mode is introduced that addresses the problem of high false alarm rates due to strong clutter discretes in the radar field of regard and leverages a MIMO probing approach to both rapidly characterize and minimize their impact on target detection performance, while minimizing impact to radar timeline.
Abstract: A new airborne radar mode is introduced that addresses the problem of high false alarm rates due to strong clutter discretes in the radar field of regard. The new mode takes advantage of emerging cognitive and fully adaptive radar (CoFAR) architectures that support rapid adaptation of the radar space-time transmit waveform. The new mode exploits this flexibility to both rapidly characterize strong clutter discretes and minimize their impact on target detection performance, while minimizing impact to radar timeline. The new mode leverages a MIMO probing approach that rapidly characterizes the clutter discretes in the scene and uses the received signals to form an appropriate space-time waveform response that minimizes their radar return and impact on radar performance during the processing of subsequent radar pulses. The paper provides details about the processing algorithms and presents a performance assessment based on a simulation of an airborne GMTI radar system.
TL;DR: Clutter suppression and inverse synthetic aperture radar (ISAR) imaging are combined to obtain high-resolution images of non-cooperative moving ground targets within SAR images and results obtained by processing a real dataset demonstrate the effectiveness of the proposed method.
Abstract: Non-cooperative moving targets appear defocused within synthetic aperture radar (SAR) images and, in the case of ground targets, the blurring effect because of the uncompensated target motion decreases the radar's detection capabilities. Ground clutter, if sufficiently strong, may also obscure individual scatterers on moving targets resulting in a decreased ability to successfully classify the target. In this study, clutter suppression and inverse synthetic aperture radar (ISAR) imaging are combined to obtain high-resolution images of non-cooperative moving ground targets within SAR images. The clutter suppression technique proposed here is ISAR application oriented and is termed space-Doppler adaptive processing. Results obtained by processing a real dataset demonstrate the effectiveness of the proposed method.
TL;DR: This work shows how to adapt standard clutter rejection techniques to work directly on the sub-Nyquist samples, allowing to preserve high detection rates even in the presence of strong clutter, while avoiding the need to first interpolate the samples to the Nyquist grid.
Abstract: Recently, a new approach to sub-Nyquist sampling and processing in pulse-Doppler radar was introduced, based on the Xampling approach to reduced-rate sampling combined with Doppler focusing performed on the low-rate samples. This method imposes no restrictions on the transmitter, reduces both the sam- pling and processing rates and exhibits linear signal-to-noise ratio improvement with the number of pulses. Here we extend previous work on sub-Nyquist pulse-Doppler radar by incorporating a clutter removal algorithm operating on the sub-Nyquist samples, allowing to reject clutter modeled as a colored Gaussian random process. In particular, we show how to adapt standard clutter rejection techniques to work directly on the sub-Nyquist samples, allowing to preserve high detection rates even in the presence of strong clutter, while avoiding the need to first interpolate the samples to the Nyquist grid.
TL;DR: An improved detector is presented that combines the following features: a better approximation to the Neyman-Pearson detector based on the GLR, and a unique CFAR detector applied to the squared modulus of the maximum filter bank output.
Abstract: Neural Networks based CFAR techniques are proposed in an improved coherent radar detector.A coherent detector using a unique CFAR is compared to the classical bank of CFAR techniques.The filter bank output is statistically analyzed to prove Gaussian CFARs unfeasibility.The proposed neural CFAR can be applied to any clutter distribution or detection strategy.A comparative study is carried out on a simulated scenario with complex target trajectories. This paper tackles the detection of radar targets with unknown Doppler shift in presence of clutter. A Neural Network based Constant False Alarm Rate (CFAR) technique is proposed for adapting the detection threshold in an improved architecture based on the Generalized Likelihood Ratio (GLR) detector. Detection schemes based on Doppler processors (Moving Target Indicator (MTI) and Moving Target Detector (MTD)) and conventional CFAR detectors are considered as reference. In these reference solutions, interference is assumed Gaussian and white at the output of each Doppler filter, so conventional incoherent CFAR detectors are applied. The outputs of the CFAR detectors are combined using an OR operation to decide the presence of a target if, at least, one of the CFARs declares it. As a result, the P FA is higher than the desired one, as we prove. In this paper, an improved detector is presented that combines the following features: a better approximation to the Neyman-Pearson detector based on the GLR (selecting the maximum filter bank output), and a unique CFAR detector applied to the squared modulus of the maximum filter bank output. Due to the non-linear nature of the maximum function, conventional CFAR detectors are not suitable. A Neural Network CFAR solution is proposed. A general design method is presented. Results prove that the designed CFAR allows the exploitation of the better detection capabilities of the detector based on the maximum function, providing a higher probability of detection while fulfilling the probability of false alarm requirement. The proposed method can be extended to other detection strategies and radar scenarios.
TL;DR: A cascaded algorithm is presented to realise clutter suppression for NSLAR with HPRF using a novel orthogonal-waveform-based elevation adaptive beamforming method and the residual range-independent far-range clutter is suppressed by azimuth-Doppler space-time adaptive processing (STAP).
Abstract: Clutter suppression is a challenging problem in non-side-looking airborne radar (NSLAR) because of the range-dependent clutter. It is more intractable when the NSLAR operates at high pulse repetition frequency (HPRF). In this study, a cascaded algorithm is presented to realise clutter suppression for NSLAR with HPRF. A novel orthogonal-waveform-based elevation adaptive beamforming method is proposed to suppress range-dependent near-range clutter at the first stage, and the residual range-independent far-range clutter is suppressed by azimuth-Doppler space-time adaptive processing (STAP) at the second stage. The proposed elevation beamformer can provide excellent performance on near-range clutter suppression because of the developed secondary data selection strategy. After suppression of the range-dependent near-range clutter, the range independency of clutter samples is enhanced evidently. Hence, the clutter suppression performance obtained by azimuth-Doppler STAP methods could be improved dramatically. Numerical examples are given to verify the validity of the proposed algorithm.
TL;DR: A spread clutter estimated canceller (SCEC) based on single notch space filter has been developed for SSC cancellation to cancel the clutter in the main-lobe with the idea of estimating the SSC in the looking direction through the ones in side-lobes.
Abstract: High-frequency surface wave radar (HFSWR) has been successfully developed for early warning, especially for monitoring the moving vessels. However, it can be blinded by space spread clutter (SSC) which can cover a wide looking directions, such as sea clutter and ionospheric clutter in HFSWR. A few methods have made great efforts for SSC cancellation, but these efforts make no sense for the clutter in main-lobe that is a long-standing problem. In this paper, a spread clutter estimated canceller (SCEC) based on single notch space filter has been developed for SSC cancellation to cancel the clutter in the main-lobe with the idea of estimating the SSC in the looking direction through the ones in side-lobes. The feasibility of the idea has been described and demonstrated by the results of simulations and measured data which make great significance for target detection and tracking.
TL;DR: The experimental results of real S-band and X-band sea clutter data show that the proposed weak target detection method is more stable, and could achieve a better detection performance under low SCR conditions.
Abstract: Weak target detection based on fractal analysis is a hot research topic. The existing methods, using single fractal dimension and Hurst exponent, are not applicable under low signal clutter ratio (SCR) conditions. This study focuses on enhancing the performance of weak target detection by utilising the multifractal properties of sea clutter. The existing global multifractal spectrum based method has limited performance because of its non-stability. Therefore this study proposes a weak target detection method by taking into account the local difference of multifractal spectrum between sea clutter with and without target. The local-multifractal spectrum is obtained by adding a rectangle window to the multifractal spectrum, and the local difference is calculated by the local mean square summation algorithm. In addition, the window length, a key parameter for obtaining the local-multifractal spectrum, is adaptively computed by the slope of the singularity intensity. In comparison with the existing multifractal spectrum based method, the experimental results of real S-band and X-band sea clutter data show that the proposed method is more stable, and could achieve a better detection performance under low SCR conditions.
10 May 2015
TL;DR: The performance of the reconstruction is analysed at this initial stage of the research, operational regimes and conditions to deliver robust and interpretable profile outline are discussed.
Abstract: This paper concerns with the practical aspects of the target profile reconstruction in a single-node ground-based forward scatter radar (FSR) system. Modelling approach for simulation of the target signal return and procedure of the target profile reconstruction are discussed. Experimental set-up and measurements are described. For the first time the reconstructed profiles of three different cars measured in real outdoor environment are demonstrated. The performance of the reconstruction is analysed at this initial stage of the research, operational regimes and conditions to deliver robust and interpretable profile outline are discussed.