Microwave Staring Correlated Imaging for Maneuvering Target Based on Sparse Bayesian Learning

Microwave staring correlated imaging (MSCI) is a novel super-resolution radar imaging technique based on temporal-spatial stochastic radiation field without the limitation of relative motion between the target and radar systems. A high-speed maneuvering target can be regarded as a moving target with constant acceleration in a short observation period. If the effect of motion is not taken into consideration, the imaging result will be blurred. To solve this problem, the target's motion parameters should be estimated along with target imaging. This paper focuses on maneuvering target imaging problem and proposes two algorithms for exact motion parameters estimation. We use adaptive grid division (AGD) method to make preliminary estimation of motion parameters. Then the exact motion parameters are obtained by the maneuvering target imaging based on iteration sparse Bayesian learning (MTI-ISBL) and maneuvering target imaging based on block sparse Bayesian learning (MTI-BSBL). The effectiveness of the proposed algorithms is verified by simulation results.