Imaging Method for Spinning Targets Based on Bayesian Compressive Sensing

Narrow-band radar which emits the signal restricted by bandwidth limitation has a low resolution in range profile so that it usually applies to target detection and tracking. However, the rotating target's micro-doppler is used to image by Narrow-band radar that provides a new idea for target recognition. Due to the characteristics of narrow-band radar echoes from spinning targets, an imaging method based on Bayesian Compressive Sensing (BCS) is proposed according to the sparsity nature of narrow-band radar echoes from spinning targets. Simulation results show that the proposed approach is able to provide a sharp and sparse image absence of side-lobes which is the common problem in conventional complex-valued back-projection method and has fewer artifacts compared to the previous version of Compressive Sensing (CS) based methods.