An Adaptive False Target Suppression and Radial Velocity Estimation Method of Moving Targets Based on Image-Domain for High-Resolution and Wide-Swath SAR

For azimuth multichannel (AMC) high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) systems, nonuniformly sampled signals will lead to false targets appearing in the image, which has a great impact on image quality and target detection. Many spectrum reconstruction methods for stationary scenes have been proposed to obtain images without false targets, but it is ineffective for moving targets due to the phase error caused by radial velocity. To present the radial velocity effect on the reconstructed image clearly, we establish a precise relation between the characteristics (imaging position, residual RCM, and amplitude) of false targets and radial velocity from the Doppler domain perspective. According to the effect analysis, we propose an image-domain false target suppression and radial velocity estimation method for moving targets. First, obtain multiple images through imaging preprocessing. Second, estimate and compensate the phase error of false targets based on the least
$L^{1}$
-norm optimization model to suppress false targets. Third, estimate the radial velocity of real moving targets based on the cross correlation method. Compared to the existing methods, the proposed method is processed in the image domain which has a high signal-to-noise ratio (SNR) with the advantages of not requiring recognition and extraction of targets, lower computational complexity, and applicability for slow targets, fast targets, and multiple targets of the same range cell. The simulated SAR data and GaoFen-3 SAR data are processed to demonstrate the effectiveness of the proposed method. Furthermore, the radial velocity estimation method is verified by automatic identification system (AIS) information.