Ground Moving Target Indication Method Research Articles

A Robust Dual-Platform GMTI Method against Nonuniform Clutter

The ground moving-target indication (GMTI) technique can detect civil and military moving targets, which means that this technique has received much attention. Strong clutter background suppression is one of the critical problems in this application. However, the detection performance in heterogeneous environment can be degraded due to the inaccurate estimation of the clutter covariance matrix (CCM). In this paper, we propose a robust GMTI method using a spaceborne dual-platform synthetic aperture radar (SAR) system, which can obtain highly accurate CCM in nonuniform clutter. Firstly, the accurate CCM is estimated based on the SAR image obtained by the former platform. Then, space–time adaptive processing (STAP) is carried out using the obtained the CCM. Finally, the detection threshold is set according to the estimated CCM and detection is executed accurately. Compared with the traditional CCM estimation method in STAP using the clutter nearby the cell under test, this method directly estimates the CCM using the clutter of the cell under test, which can avoid CCM estimation mistakes in heterogeneous clutter environment. The clutter can be whitened and depressed more effectively. Additionally, with the accurate threshold acquired from the CCM, the detection probability can be effectively improved under a certain false-alarm criterion. Based on simulation data, GMTI experiments in a heterogeneous environment such as clutter with strong pollution, junction zone of hot and cold clutter, and clutter with nonuniform power are carried out; the results show that the moving targets can be effectively detected with the proposed method.

A SAR‐GMTI method based on changes of polarization characteristics before and after clutter suppression

Due to the azimuth shift and defocus of the moving targets in the synthetic aperture radar image domain, a new synthetic aperture radar ground moving target indication method is proposed in this letter based on the changes of moving targets’ polarization characteristics before and after clutter suppression. This method can effectively suppress the false alarms caused by the man-made objects compared with the displaced phase centre array method in the complex scenes. Finally, the effectiveness of the proposed method is verified by the real multi-channel quadrature-polarimetric synthetic aperture radar data.

Joint Tracking of Moving Target in Single-Channel Video SAR

Video synthetic aperture radar (SAR) has been found very useful in ground moving target indication (GMTI) and tracking. The dynamic shadows in video SAR imagery sequences indicate the real positions of moving targets, which can be utilized in target detection and tracking. Unfortunately, the shadow-based method often fails when the shadows are not sufficiently developed. On the other hand, the traditional energy-based GMTI methods exhibit performance degradation when SAR images of a moving target are distorted or smeared. Neither of these two methods can stand alone to provide robust detection and tracking of moving targets. This article presents a joint processing framework for video SAR GMTI and tracking by combining the target shadow and echo energy information, which effectively lowers the false alarm and miss-detection rate. This approach is very suitable for real-time surveillance of ground moving targets in a single-channel video SAR system. The proposed approach has been verified by using the simulated and the real video SAR data.

Multichannel SAR Moving Target Detection via RPCA-Net

Ground moving target indication (GMTI), as a challenging task for synthetic aperture radar (SAR) systems, keeps drawing considerable attention. Robust principal component analysis (RPCA) aiming at separating low-rank and sparse components has been successfully employed in SAR systems for GMTI recently. However, its practical application is limited by the heavy computational burden as well as the requirement of manual parameter modification. To cope with this problem, a fast and free of presetting parameters RPCA network (RPCA-Net) is proposed for SAR-GMTI under strong clutter background. In the proposed method, a novel RPCA model is first introduced, where not only the low-rank and sparse terms but also the errors in practical SAR systems are taken into account. Moreover, the low-rank factorization plus scaled gradient descent (ScaledGD) is also employed to acquire low-rank clutter background rather than singular value decomposition (SVD). Then, we parameterize our proposed RPCA model and unfold it as a feedforward neural network (FNN) to acquire the iterative parameters through backpropagation. Compared to the GMTI methods based on traditional RPCA models, our proposed RPCA-Net can provide a higher detection ability and faster convergence without presetting parameters empirically. Experiments on two groups of measured data collected by airborne SAR systems validate the superior performance of the proposed RPCA-Net.

A Study on the Range Equation Modeling for Multichannel Medium-Earth-Orbit SAR-GMTI Systems

This paper studies the range equation modeling of a ground moving target for multichannel medium-Earth-orbit (MEO) synthetic aperture radar (SAR) ground moving target indication (GMTI), an issue which is challenging to tackle due to the non-linear motion of the radar platform and the Earth rotation. In the paper, the coordinates of the multichannel MEO SAR and the target, as well as the target’s range equation with respect to each channel, are developed. Moreover, an expression of concise form is derived for the target’s quadratic-approximated range equation, which will benefit the design of GMTI methods. Furthermore, theoretical analyses are conducted to reveal the dependency between the accuracy of the quadratic-approximated range equation and the parameters of the radar and the target. Numerical simulations are carried out to investigate the influence of the quadratic approximation of the range equation on the GMTI performance and to figure out the quadratic-approximated range equation’s scope of application.

CV-GMTINet: GMTI Using a Deep Complex-Valued Convolutional Neural Network for Multichannel SAR-GMTI System

Motivated by recent advances in deep learning, a novel deep complex-valued convolutional neural network (CV-CNN)-based method is proposed for ground moving target indication (GMTI) in a multichannel synthetic aperture radar (SAR) system. The proposed method integrates the SAR-GMTI task into a blind inverse problem solved by a deep CV-CNN named CV-GMTINet. To take advantage of the amplitude and phase information of complex multichannel SAR images, both feature maps and network parameters are extended into the complex domain. The proposed CV-GMTINet is designed by adopting complex-valued residual dense blocks (CV-RDBs) to adaptively learn complex hierarchical features. The trained CV-GMTINet, as a GMTI processor, can be applied to complex multichannel SAR images to discriminate moving targets from stationary clutter and refocus the moving target images simultaneously. Experiments on TerraSAR-X data show that the proposed method achieves significant improvements over existing state-of-the-art GMTI methods in both detection performance and refocusing accuracy, especially for the slow-moving target and the moving target with only along-track velocity.

Azimuth Multichannel GMTI Based on Ka-Band DBF-SCORE SAR System

The azimuth multichannel synthetic aperture radar (SAR) system is used in ground moving target indication (GMTI). But for Ka-band SAR, the conflicts between high gain and wide swath coverage are very strict. The digital beamforming (DBF) scan-on-receive (SCORE) algorithm can solve this problem very well. This letter introduces a multichannel SAR system with three receiving antennas in the azimuth direction. For each azimuth antenna, eight subapertures are arranged in the elevation direction in order to obtain higher gain and a lower data rate through the DBF-SCORE algorithm. Airborne flight experiments with this system are accomplished successfully and quantities of experimental data are acquired. In this letter, we first derive the signal forms and weighting coefficients in the DBF-SCORE procedures. Then, different GMTI methods including along-track interferometry and displaced phase center antenna are introduced for azimuth multichannel SAR–GMTI based on the DBF-SCORE technology. Finally, airborne raw data with cooperating moving targets are processed successfully, and the estimation errors of the radial velocities meet the expected accuracy requirements.

Local Detection of Moving Targets in SAR Image Based on NRS Hypotheses

Ground moving target indication (GMTI) is one of the important applications of synthetic aperture radar (SAR). This paper introduces a GMTI method for local detection of the ground moving targets in SAR image based on normalized relative speed (NRS) hypotheses. The input of the GMTI method is a complex SAR image where areas of interest for GMTI are locally selected. The output of the method includes the detected targets, the NRSs with respect to the SAR platform, the locations where the detected targets are focused, and the SAR images of the detected targets. The mathematical background of the GMTI method is presented in detail. The method is validated with the data delivered by the Coherent All-Radio Band Sensor, an airborne ultrawideband-ultrawidebeam low-frequency SAR system. The shortcomings of the introduced method are investigated and followed with the solutions.

Clutter suppression and GMTI for hypersonic vehicle borne SAR system with MIMO antenna

This study proposes a clutter suppression approach and the corresponding ground moving target imaging algorithm for hypersonic vehicle (HSV) borne synthetic aperture radar (SAR) system with multiple-input-multiple-output (MIMO) antenna. HSV-borne radar platforms fly with a high speed, which can lead to severe Doppler ambiguity, and the radar system usually cannot provide enough channel freedom degree for clutter suppression. In this study, an SAR ground moving target indication (GMTI) approach with MIMO antenna is presented for HSV-borne radar. Compared with the traditional multichannel SAR GMTI methods, the proposed approach can provide more space freedom degree and obtain a wider imaging swath without decreasing pulse repetition frequency. Besides, the improved deramp space-time adaptive processing method decreases the ambiguity times of the ground clutter and focuses the moving target. The simulation results validate the effectiveness of the proposed method.

Improved Ground Moving Target Indication Method in Heterogeneous Environment With Polarization-Aided Adaptive Processing

Adaptive ground moving target indication (GMTI) algorithms based on the sample matrix inversion require the availability of a secondary data (training data) set to determine the adaptive filter. A polarization-aided GMTI method is devised in this letter for selecting this training data, which could improve the detection performance in heterogeneous environments. In particular, improved classification results are first obtained with the proposed polarization-space 2-D Wishart classifier, which are then employed in a generalized inner product algorithm to select the secondary data. The proposed scheme is able to provide a better choice of secondary data, resulting in considerable improvement in detection performance. Numerical results are provided to show the effectiveness of the proposed method.

SAR Ground Moving Target Indication Based on Relative Residue of DPCA Processing.

For modern synthetic aperture radar (SAR), it has much more urgent demands on ground moving target indication (GMTI), which includes not only the point moving targets like cars, truck or tanks but also the distributed moving targets like river or ocean surfaces. Among the existing GMTI methods, displaced phase center antenna (DPCA) can effectively cancel the strong ground clutter and has been widely used. However, its detection performance is closely related to the target’s signal-to-clutter ratio (SCR) as well as radial velocity, and it cannot effectively detect the weak large-sized river surfaces in strong ground clutter due to their low SCR caused by specular scattering. This paper proposes a novel method called relative residue of DPCA (RR-DPCA), which jointly utilizes the DPCA cancellation outputs and the multi-look images to improve the detection performance of weak river surfaces. Furthermore, based on the statistics analysis of the RR-DPCA outputs on the homogenous background, the cell average (CA) method can be well applied for subsequent constant false alarm rate (CFAR) detection. The proposed RR-DPCA method can well detect the point moving targets and distributed moving targets simultaneously. Finally, the results of both simulated and real data are provided to demonstrate the effectiveness of the proposed SAR/GMTI method.

A Ground Moving Target Indication Method Based on Compressive Sensing

针对实际非均匀环境空时自适应处理(STAP)难以获取足够独立同分布样本的问题，该文提出一种基于压缩感知的运动目标检测方法。该方法首先将待检测距离门的回波数据变换至2维频率域进行能量积累，并构造相应2维频率域的冗余字典，然后利用贝叶斯压缩感知技术提取若干强静止散射点谱峰，估计杂波谱能量支撑区，最后通过基于加权的最小l1范数优化模型实现杂波抑制与运动目标检测。理论分析及仿真实验结果表明该方法具有较高的角度和多普勒分辨率，并且在低信噪比情况下也可以获得良好的检测效果。

Ground Moving Target Indication Using an InSAR System With a Hybrid Baseline

In this letter, a two-channel airborne experimental interferometric synthetic aperture radar (InSAR) designed for terrain height estimation is exploited to acquire the ability of ground moving target indication (GMTI). Due to the hybrid baseline of this system, the interferometric phase changes with the target motion as well as the terrain height. The fluctuation of the interferometric phase worsens the performance of the clutter suppression and the radial velocity estimation. In order to resolve this problem, a GMTI method with three steps is proposed. After two steps are used to eliminate the local flat-Earth phase and the cross-track interferometric phase of the scene, respectively, an adaptive filtering method is used to suppress the stationary clutter with the benefit of calibrating the sensor responses. A conventional constant false alarm rate detector is then used to indicate the moving targets. The validity of the proposed method is demonstrated with real data collected using an experimental airborne InSAR system.