稀疏阵列MIMO雷达高精度收发角度联合估计

提出一种基于孔径扩展的稀疏阵列MIMO雷达高精度收发角度估计算法. 采用收、发阵列均为稀疏线性分布式子阵的双基地MIMO雷达系统,通过非均匀阵列设计,利用Khatri-Rao乘积运算实现收发阵列中阵元间短基线和子阵间长基线的同时虚拟扩展. 对接收数据进行降冗余和数据平滑处理,利用双尺度酉ESPRIT算法解周期性模糊,得到无模糊的高精度收发角度估计. 与传统算法相比,所提出的算法在不增加天线数目和硬件复杂度的情况下可有效扩展MIMO雷达的阵列孔径,在实现多目标收发角度联合估计的同时获得更高的参数估计性能. 仿真结果验证了阵列虚拟扩展和算法方位估计的有效性.

Joint DOD and DOA Estimation with High Accuracy in Bistatic MIMO Radar Using Sparse Array

Based on extended aperture of bistatic MIMO radar using asparse array, a joint high accurate method for estimating direction of arrival (DOA) and direction of departure (DOD) is proposed. A bistatic MIMO radar with sparse linear distributed subarrays and dual baselines for both transmission and receiving is used. By designing a nonuniform linear array and using Khatri-Rao product processing, the long baseline of inter-subarray spacing and short baseline of inter-sensor spacing in the transmission/receiving arrays are virtually extended simultaneously. With the redundancy removal and spatial smoothing for the received data, high accuracy estimation of DOA and DOD are accomplished using a dual-size unitary ESPRIT algorithm for angular ambiguities resolution. Compared with conventional algorithms, the proposed method can achieve virtual extension of aperture for the MIMO radar without increasing the number of sensors and computational complexity while achieving effective estimation for transmitting and receiving angle with better performance. Simulation results show effectiveness of the proposed method.