基于稀疏表示的杂波建模和微弱运动目标探测

Small Moving Target Detection Using Sparse Clutter Modeling

雷达回波中,微弱运动目标会被强杂波掩盖,造成目标探测困难。文中提出基于匹配追踪稀疏表示方法的雷达微弱运动目标探测算法,采用训练的过完备字典线性组合对杂波进行建模并解决稀疏表示问题,提高了杂波建模的准确性,利用杂波模型抑制杂波,可以从杂波背景中有效地探测微弱目标。仿真结果表明:文中提出的算法优于传统的目标探测方法,可以提高杂波抑制和微弱运动目标探测性能。

Radar target echo is usually under very strong background of clutters.The detection of small moving targets has been a difficult problem.Based on matching pursuit sparse representation technology, a novel radar small moving target detection algo-rithm is proposed in this paper.Firstly, by using the correlation and sparsity characteristics of radar clutters, the proposed algo-rithm modeling clutters as linear combinations of a trained over-complete dictionary, successfully improves the accuracy of clutter modeling.Then upon employing this model in the clutter suppression, targets can be detected effectively from background clutters. Simulation results confirm that the performance of this method outperforms the classical target detection algorithms and this algo-rithm can improve the results of small moving target detection.