基于3D-OMP算法的SAR动目标成像方法

A SAR Moving Target Imaging Method Based on 3-Dimensional Orthogonal Matching Pursuit Algorithm

针对稀疏场景下的SAR动目标成像问题展开研究,提出一种基于三维正交匹配追踪(3D-OMP)算法的稀疏成像方法。首先对成像区域进行网格划分,然后以运动目标的二维速度作为动态参数构建三维稀疏字典矩阵,即参数化稀疏表征。在算法迭代过程中,通过计算回波数据矩阵与三维稀疏字典矩阵各层之间的相关度筛选出信号的支撑集。最后利用最小二乘准则,计算出支撑集下目标场景的稀疏表征系数。该3DOMP算法是经典OMP算法的改进与拓展,因此继承了OMP算法计算复杂度低、信号稀疏特征增强明显的优势,同时具备了重构SAR动目标图像的能力。仿真实验结果验证了该SAR动目标成像方法的有效性。

In view of SAR moving target imaging on the sparse scenes,a sparse imaging method is proposed based on 3-dimensional orthogonal matching pursuit(3D-OMP)algorithm.In this method,the imaging area is first gridded,and then the 3-dimensional sparse dictionary matrix is constructed with the 2D motion speed of the moving target being taken as the dynamic parameter,i.e.the parametric sparse representation.In the iteration process,the support set of signals is filtered from calculating the correlation between the echo data matrix and each layer of the 3-dimensional sparse dictionary matrix.Finally,the sparse representation coefficient on the target scene under the condition of support set is calculated by using the least square criterion.The proposed 3D-OMP algorithm is an improvement and expansion of the classical OMP algorithm,inherits the advantages of OMP algorithm,such as low computational complexity,obvious signal sparse feature enhancement,and simultaneously has the ability to reconstruct SAR moving target images.The simulation results show that the proposed SAR moving target imaging method is valid.