Wang Xianpeng, Wang Wei, Li Xin, Liu Jing
College of Automation, Harbin Engineering University, No. 145 Nantong Street, Harbin 150001, China.
Sensors (Basel). 2015 Nov 10;15(11):28271-86. doi: 10.3390/s151128271.
In this paper, a real-valued covariance vector sparsity-inducing method for direction of arrival (DOA) estimation is proposed in monostatic multiple-input multiple-output (MIMO) radar. Exploiting the special configuration of monostatic MIMO radar, low-dimensional real-valued received data can be obtained by using the reduced-dimensional transformation and unitary transformation technique. Then, based on the Khatri-Rao product, a real-valued sparse representation framework of the covariance vector is formulated to estimate DOA. Compared to the existing sparsity-inducing DOA estimation methods, the proposed method provides better angle estimation performance and lower computational complexity. Simulation results verify the effectiveness and advantage of the proposed method.
本文针对单基地多输入多输出（MIMO）雷达，提出了一种用于波达方向（DOA）估计的实值协方差向量稀疏诱导方法。利用单基地MIMO雷达的特殊配置，通过降维变换和酉变换技术可获得低维实值接收数据。然后，基于Khatri-Rao积，构建了协方差向量的实值稀疏表示框架来估计DOA。与现有的稀疏诱导DOA估计方法相比，该方法具有更好的角度估计性能和更低的计算复杂度。仿真结果验证了该方法的有效性和优势。
