MULTIPLE-OVERLAID-TARGETS SEPARATION AND HIGH PRECISION VELOCITY ESTIMATION BASED ON BAYESIAN CRITERION IN VSAR SYSTEM

For the velocity synthetic aperture radar (VSAR) system, the velocity spectrum is obtained along the multichannel direction to separate multiple moving targets and to estimate their velocities, which is important for applications like traffic flows monitoring. On urban roads, vehicles usually appear closely with minor velocity difference, making them overlaid in the spectrum, resulting in that multiple overlaid targets are wrongly recognized as one target. To solve it, we present a multiple-overlaid-targets separation and high precision velocity estimation approach based on Bayesian criterion. Therein, velocity spectrum is reconstructed utilizing its sparsity, where the targets are separated. And their velocities are estimated precisely afterwards. Compared with the current popular approach based on MUSIC algorithm, numerical experiments show that, via the proposed one, three overlaid moving targets are separated clearly, with higher velocity resolution being obtained. And all their velocities are estimated with high precision, even in the low SNR case.