基于改进OMP算法的稀疏目标微波关联成像方法

利用稀疏重构类方法进行雷达微波关联成像时, 传统的正交匹配追踪(orthogonal matching pursuit, OMP)算法在每一次迭代过程中均需要求解目标函数的最小二乘解, 导致成像算法计算复杂度随矩阵规模和迭代次数增加而急剧攀升。针对此问题, 结合频率捷变思想, 提出了一种改进OMP算法的稀疏目标微波关联成像方法。首先, 阐明了微波关联成像机理, 并构建了微波关联成像信号模型; 然后, 利用共轭梯度法对OMP算法中的最小二乘求解步骤进行了改进, 并分析了改进后算法的计算量; 最后, 通过与最小二乘成像方法、匹配滤波成像方法和基于传统OMP稀疏重构的成像方法进行计算机对比仿真实验, 证明了本文算法的正确性与优越性。

Microwave correlation imaging method based on improved OMP algorithm for sparse targets

When sparse reconstruction method is used for radar microwave correlation imaging, the traditional orthogonal matching pursuit (OMP) algorithm needs to solve the least square solution of the objective function in each iteration, which leads to a sharp increase in the computational complexity of the imaging algorithm with the increase of the matrix size and the number of iterations. In order to solve this problem, an improved OMP microwave correlation imaging method for sparse targets combined with frequency agility. Firstly, the mechanism of microwave correlation imaging is clarified, and the signal model of microwave correlation imaging is constructed. Then, the least square solution step of OMP algorithm is improved by using conjugate gradient method, and the calculation amount of the improved algorithm is analyzed. Finally, the correctness and superiority of the proposed algorithm is verified by comparative simulation experiments with least square imaging method, matched filtering imaging method and imaging method based on traditional OMP coefficent reconstruction.