Abstract
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.
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