基于空域稀疏性的嵌套MIMO雷达DOA估计算法

A Spatial Sparsity-based DOA Estimation Method in Nested MIMO Radar

针对传统MIMO雷达可分辨目标数受限于虚拟阵元数的问题,该文提出一种基于嵌套阵的MIMO雷达阵形设计新方法并改进了相应的稀疏DOA估计算法。首先分析对传统MIMO雷达的虚拟阵元进行嵌套采样给DOA估计性能带来的影响;然后提出嵌套MIMO雷达阵形设计方法,在虚拟阵元数相同的情况下,该阵形比传统阵形分辨更多的目标;最后提出一种基于空域稀疏性的嵌套MIMO雷达改进DOA估计算法,该算法使用噪声子空间加权,在提高分辨率的同时可以有效消除伪峰。仿真结果验证了该文算法的有效性和优越性。

The maximum number of targets that can be uniquely identified by the traditional MIMO radar is limited by the number of virtual sensors. To alleviate this issue, a novel antenna array in MIMO radar which is based on the concept of nested arrays is designed in this paper, and a modified spatial sparsity-based Direction-Of-Arrival （DOA） estimation method is proposed. First, the effect of nested sampling with application to virtual array of traditional MIMO radar on the DOA estimation performance is analyzed. Second, the method to design antenna array of nested MIMO radar is proposed. It is proven that nested MIMO radar can detect more targets than traditional MIMO radar when they share the same number of virtual sensors. Finally, a modified spatial sparsity-based approach to DOA estimation in nested MIMO radar is proposed based on noise subspace weighted minimization problem, which can increase resolution and effectively suppress spurious peaks. Extensive simulation results demonstrate the effectiveness and superiority of the proposed methods.