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.

Strong Clutter Suppression via RPCA in Multichannel SAR/GMTI System

Clutter suppression and ground moving target indication (GMTI) are challenging tasks for multichannel synthetic aperture radar (MC-SAR) systems. In recent years, robust principal component analysis (RPCA), such as the augmented Lagrange multiplier method (ALM) and go decomposition (GoDec) algorithm, has drawn considerable attention for its excellent performance in distinguishing the different parts from a set of correlative database. In this letter, an efficient along-track interferometry GoDec (ATI-GoDec) approach is proposed for GMTI in MC-SAR systems under a strong clutter background. The proposed method can be separated into two sections: the predetection and the postdetection. The predetection by an efficient ATI RPCA method can decrease missing targets, and postdetection with a novel magnitude and phase (M&P) detection has the ability to reduce the false targets. As a result, the proposed method can provide a more robust performance by a comparison to the traditional ATI detection. It can also widen the tolerant values of the preset cardinality and decrease the probability of false alarm compared with the conventional GoDec algorithm. Moreover, the proposed method only takes several iterations to reach the convergence by solving the optimization problem of the RPCA model, which makes it more efficient than the previous RPCA methods. The results by applying the proposed method into a set of real SAR data are consistent with the analysis presented in this letter.

Moving Target Detection via Efficient ATI-GoDec Approach for Multichannel SAR System

Conventionally, a single-channel synthetic aperture radar (SC-SAR) system can hardly detect weak moving targets simply. In this paper, a time-Doppler chirp-varying (TDCV) filter is proposed for ground moving target indication and parameter estimation with the airborne SC-SAR system. The proposed method is easy to implement and mainly includes three steps. First, a traditional 2-D frequency range-Doppler algorithm is used to generate an original image. Second, the second-order range cell migration (RCM) phase term is partly compensated in the range frequency and azimuth time domain, and the rest of second-order RCM phase term is compensated in 2-D frequency domain. The whole processing, which is referred to as the TDCV approach, is employed to acquire a new TDCV image. Third, compared the original image with the new image, the clutter scatterers are nearly motionless while the moving targets are translated along the range direction due to their nonzero radial velocities. After the cancellation between two normalized images, the clutter background would be significantly suppressed since the two images generated by the same data. As a result, the moving targets can be indicated and the range difference of the moving target between two images can be exploited to estimate their radial velocities. The results obtained by applying the proposed method into a set of real SAR data are consistent with the analysis presented in this paper.

GMTI and Parameter Estimation via Time-Doppler Chirp-Varying Approach for Single-Channel Airborne SAR System

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

An Improvement in Multichannel SAR-GMTI Detection in Heterogeneous Environments

This paper develops a framework based on enhanced shadow-aided decision for multichannel synthetic aperture radar-based ground moving target indication system according to the relationships between the moving target and its shadow information in position, dimensions, and intensity. As a sort of feature information available, the moving target shadow may improve the ground target detection performance. A critical precondition for shadow utilization is to obtain the good detection performance for the moving target shadow. However, shadow detection performance will deteriorate inevitably as a result of target motion that blurs its shadow. To address this issue, a knowledge-aided shadow detection algorithm with adaptive thresholds is proposed to improve the shadow detection performance in the developed framework. Furthermore, the theoretical performance analysis is performed, which indicates that the proposed knowledge-aided shadow detection algorithm has a better performance than that of the conventional shadow detection algorithm with a fixed threshold. Finally, numerical simulation experiments are presented to demonstrate that the developed framework can obtain good results for extended ground moving target detection.

An Extended Moving Target Detection Approach for High-Resolution Multichannel SAR-GMTI Systems Based on Enhanced Shadow-Aided Decision

For multichannel synthetic aperture radar based ground moving-target indication (SAR-GMTI), the effective baseline usually needs to be estimated in order to obtain an accurate estimate of radial velocity for each moving target. This paper deals with the effects of Doppler aliasing on baseline estimation. We show that Doppler aliasing can introduce an interferometric phase uncertainty as well as an interferometric phase bias. The phase uncertainty will increase the variance of the baseline estimate, whereas the phase bias will bias the baseline estimate. To address the aforementioned effects caused by Doppler aliasing, a new method for estimating the effective baseline is proposed. One of the key steps of this method is to perform an operation called sample censoring aimed at mitigating the problem of estimation bias. The censoring threshold can be approximately determined by introducing a concept referred to as equivalent variance for the interferometric phases of the entire Doppler bins. Moreover, in order to account for the variation of interferometric phase variance over different Doppler bins, a strategy of weighting is adopted. Experimental results from SAR-GMTI data validate the effectiveness of the newly proposed baseline estimation method.

Effects of Doppler Aliasing on Baseline Estimation in Multichannel SAR-GMTI and Solutions to Address These Effects

For interferometric synthetic aperture radar (InSAR), the second moment of interferometric phase, i.e., its variance, is a useful metric for InSAR applications (e.g., configuration design). Due to the high degree of nonlinearity in the probability density function of the multilook interferometric phase, it is extremely difficult to derive the analytical expression of the interferometric-phase variance as a function of the number of looks. However, in this letter, we will show that, if we follow an indirect route, then an analytical formula for approximating the interferometric-phase variance for any number of looks can be obtained. The key step of deriving this analytical formula is to transform the interferometric phase into the Euler domain. Simulation results show an excellent agreement between the measured variance curve and the curve obtained by the newly proposed formula except for some small coherence values.

Fengyang Shen

Papers

An Improvement in Multichannel SAR-GMTI Detection in Heterogeneous Environments

Effects of Doppler Aliasing on Baseline Estimation in Multichannel SAR-GMTI and Solutions to Address These Effects

An Analytical Formula Approximating the Multilook Interferometric-Phase Variance for InSAR