基于时空结构的双基MIMO雷达多维参数联合估计

为了充分利用目标的时域特性来改善双基多输入多输出(MIMO)雷达波达方向(DOA)和离波方向(DOD)的估计性能,探讨了双基MIMO雷达在时-空模型下的多维参数联合估计问题。针对慢动目标,基于多维旋转不变技术信号参数估计(ESPRIT)算法,同时利用时域相邻两级延迟包含的时间相位差、发射阵列相邻阵元包含的空间相位差以及接收阵列相邻阵元包含的空间相位差作为旋转因子,形成旋转不变子空间,再根据矩阵、矩阵的特征值及特征值对应的特征向量三者之间的关系解决了参数配对问题,实现了三维参数联合估计。该方法在信噪比低、积累脉冲数少时,目标的DOA与DOD估计性能比不利用时域特性时有明显改善。仿真结果验证了本方法的有效性。

Multi-dimensional Parameter Joint Estimation of Bistatic MIMO Radars Based on Temporal-spatial Structure

For the purpose of improving the direction of arrival (DOA) and direction of departure (DOD) estimation performance for a bistatic multiple-input multiple-output (MIMO) radar by making the best use of the target temporal structures, this article investigates multi-dimensional parameter joint estimation for bistatic MIMO radar based on a 2-dimension temporal-spatial model. For slowly moving targets, a rotational invariant subspace is formed which is based on the multi-dimensional estimation of signal parameters by rotational invariance techniques (ESPRIT) by means of the rotational factors produced by the phase shifts due to the adjacent delays in the time domain and the adjacent transmitting and receiving of array elements respectively, and the parameter matching is solved according to the tripartite relationships among the matrix, the eigenvalue of the matrix and the eigenvector of the corresponding eigenvalue. Then the 3D parameter joint estimation is implemented. The method outperforms the conventional ESPRIT method which does not make use of signal temporal structure in the case of less accumulative pulses and low singal to noise ratio (SNR). Simulation results prove the validity of the method.