【摘要】 基于对双基地MIMO雷达目标进行定位的目的,本文采用本征值分解方法对接收信号的相关矩阵进行分解,得到噪声信号子空间,并用之替代传统的线性预测算法中的接收信号空间,降低了运算复杂度。通过仿真分析,在90°×90°的密集空间里,估计出了3个目标的波达方向和波离方向,并且每个目标的波达方向和波离方向自动匹配。在小快拍数和低信噪比环境下,改进后的算法与传统的线性预测算法相比,具有更高的目标定位精度。仿真结果验证了该算法的有效性。更多还原

【Abstract】 In order to locate the targets of bistatic multiple-input and multiple-output(MIMO)radar,the signal correlation matrix is processed by eigenvalue decomposition(EVD)and a noise subspace is obtained. Then,the signal correlation matrix in the traditional linear prediction(LP) algorithm is replaced by the noise subspace,which reduces the computation complexity. In the 90°×90° intensive space,the direction of departure(DOD)and direction of arrival(DOA)of all the three targets are estimated and are paired automatically. In low SNR and small snapshots,the localization performance of the improved method outperforms that of the traditional linear prediction. Simulations results verify the effectiveness of the method.更多还原