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Video synthetic aperture radar (VideoSAR) can detect and identify a moving target based on its shadow. A slowly moving target has a shadow with distinct features, but it cannot be detected by state-of-the-art difference-based algorithms because of minor variations between adjacent frames. Furthermore, the detection boxes generated by difference-based algorithms often contain such defects as misalignments and fracture. In light of these problems, this study proposed a robust moving target detection (MTD) algorithm for objects on the ground by fusing the background frame detection results and the difference between frames over multiple intervals. We also discuss defects that occur in conventional MTD algorithms. The difference in background frame was introduced to overcome the shortcomings of difference-based algorithms and acquire the shadow regions of objects. This was fused with the multi-interval frame difference to simultaneously extract the moving target at different velocities while identifying false alarms. The results of experiments on empirically acquired VideoSAR data verified the performance of the proposed algorithm in terms of detecting a moving target on the ground based on its shadow. [ABSTRACT FROM AUTHOR]

The high-resolution low frequency synthetic aperture radar (SAR) has serious range-azimuth phase coupling due to the large bandwidth and long integration time. High-resolution SAR processing methods are necessary for focusing the raw data of such radar. The generalized chirp scaling algorithm (GCSA) is generally accepted as an attractive solution to focus SAR systems with low frequency, large bandwidth and wide beam bandwidth. However, as the bandwidth and/or beamwidth increase, the serious phase coupling limits the performance of the current GCSA and degrades the imaging quality. The degradation is mainly caused by two reasons: the residual high-order coupling phase and the non-negligible error introduced by the linear approximation of stationary phase point using the principle of stationary phase (POSP). According to the characteristics of a high-resolution low frequency SAR signal, this paper firstly presents a principle to determine the required order of range frequency. After compensating for the range-independent coupling phase above 3rd order, an improved GCSA based on Lagrange inversion theorem is analytically derived. The Lagrange inversion enables the high-order range-dependent coupling phase to be accurately compensated. Imaging results of P- and L-band SAR data demonstrate the excellent performance of the proposed algorithm compared to the existing GCSA. The image quality and focusing depth in range dimension are greatly improved. The improved method provides the possibility to efficiently process high-resolution low frequency SAR data with wide swath. [ABSTRACT FROM AUTHOR]