Synthetic aperture radar (SAR) ground moving target indication (GMTI) has attracted a lot of interest from researchers for its ability of simultaneously obtaining high-quality images of stationary scenes and detection of moving targets. In recent years, the research on moving target tracking besides detection by using SAR-GMTI has also raised interest. Compared with standard SAR, the long observation time of circular SAR (CSAR) makes it possible for moving target trajectory reconstruction. By using a prior knowledge of the road information, an effective method for moving target trajectory reconstruction in single-channel CSAR is proposed in this paper. First, the radar echo is segmented according to subapertures, and the Doppler filtering is performed on each subaperture echo for clutter suppression. Second, the range walk induced by target motion is compensated by the keystone transform, and trajectories in range-Doppler domain are obtained. Last, the moving target trajectory in ground coordinate is reconstructed by using the dynamic programming algorithm with road information restrain. Experimental SAR data processing results show that the method is effective for the moving target trajectory reconstruction.

Synthetic aperture radar ground moving target indication (SAR-GMTI) is an attractive mode for radar system to obtain high-resolution regional images and detection of moving targets simultaneously. Moreover, the 360° observation capability of circular SAR (CSAR) makes it possible for moving target trajectory reconstruction. In order to address the problem that slow-moving targets, which are buried in strong stationary ground clutter, are difficult to be detected, a framework of multichannel SAR-GMTI is presented in this article. For ground moving target detection in the presence of stationary clutter, the proposed method first adopts clutter suppression interferometry and relaxation-based cyclic algorithm to suppress clutterand retrieve parameters (e.g., radial velocity and Doppler information). Then, to further reduce the false alarm rate, multiple moving target tracking algorithm is performed in range–Doppler domain. Finally, the moving target trajectory is reconstructed by using the proposed two-stage parameter estimation method based on Doppler characteristic and CSAR geometry, and the mathematical analysis of this method is performed. The proposed method is robust and insensitive to the signal-to-noise ratio. It does not rely on priori road information, so it has wide applicability, especially in military application. In addition, the framework is performed in echo domain and independent of imaging processing. The experimental results on simulated data are presented to evaluate the estimation accuracy of the proposed method, and the real data processing results are provided to demonstrate the validity and feasibility of the proposed method.

Ground moving targets with complex motions often appear seriously dislocated and smeared in synthetic aperture radar (SAR) imagery due to non-cooperative motion. Refocusing such targets in SAR is challenging because of unknown motion parameters. In this paper, a novel SAR moving target imaging method based on adaptive phase tracking (MTIm-APT) is proposed. First, the Hough transform (HT) and the second(2nd)-order Keystone transform (SOKT) are performed to correct the range migration. Second, the Doppler phase can be adaptively tracked based on the improved extended Kalman filter (EKF). With the tracked Doppler phase, the motion parameters required for moving target imaging is estimated. Finally, the moving target is well-focused after motion parameters compensation since the high-order Doppler phase errors are efficiently eliminated. Unlike existing research that only considers the 2nd- or third(3rd)-order Doppler phase, the proposed method considers higher-order Doppler parameters which can be simultaneously estimated, thus eliminating error propagation effect. More importantly, due to the suboptimal filtering characteristics of EKF, the proposed method maintains excellent imaging performance at lower signal-to-noise ratio (SNR) than classical PGA. On the other hand, our method has a certain advantage in computational efficiency. Both simulated and real data processing results are provided to validate the feasibility and effectiveness of the proposed SAR MTIm-APT method.

The polar format algorithm (PFA) is a frequency-domain algorithm with high computational efficiency especially for the high resolution imaging applications in wide-angle staring synthetic aperture radar (WAS-SAR). Because of the image distortion and defocus caused by plane wave assumption, the effective imaging scene is limited to a small region which is defined as the defocus-negligible region. In this article, a novel sub-block imaging algorithm which first applied to WAS-SAR is proposed. This method combines sub-block imaging and spatially variant post-filtering (SVPF) which can not only effectively extend the depth of focus of PFA but also greatly reduces the computational burden. What's more, the method of mosaic image is proposed in this article which can eliminate discontinuity between adjacent sub-blocks. First, the large scene is segmented into multiple regions along range direction and the size of each region is still larger than that of the defocus-negligible region. Second, refocusing is implemented by a phase compensation of the already de-chirped signal with the center of sub-blocks, respectively, and each sub-block image is formed by PFA. Third, the region in each sub-block that exceeds the defocus-negligible region is corrected by SVPF and the image distortion can be corrected by 2-D interpolation. Finally, the mosaic image method is applied to get the large-scene image with high quality. The algorithm proposed in this article is efficient and solves the problems in the process of SAR image mosaic such as dislocation and grayscale differences. The simulated and experimental data results demonstrate the effectiveness and practicability of the proposed algorithm.

Recently, the parameter estimation and focusing of ground moving target in the circular SAR (CSAR) attracts widely interest in researchers. In this paper, a sub-aperture-based frequency domain algorithm that divides the CSAR trajectory into sub-apertures is proposed, which achieves better focusing quality than that of the traditional straight-line fitting method. Firstly, the CSAR sub-aperture is fitted by a parabola with special curvature, and the effectiveness of this fitting is analyzed. Next, a parameter estimation method is proposed to estimate the motion parameters of the ground moving target for each sub-aperture. Finally, the moving target is refocused based on the estimation results. Simulation as well as the real CSAR data processing results verified the theoretical analysis of the proposed method.