非均匀矩形阵列下双基地MIMO雷达目标定位方法

Multi-target Localization Method for Bistatic MIMO Radar Using Nonuniform Rectangular Array

该文针对双基地MIMO雷达发射端、接收端皆为非均匀矩形阵列配置情况,将MIMO技术和最小冗余阵列相结合,提出基于双重孔径自由度扩展的目标发射俯仰角、发射方位角、接收俯仰角、接收方位角4参数联合估计新算法。首先利用矩阵Khatri-Rao积的运算特性,构造出2个置换矩阵,对接收信号进行矢量行变换,再通过数据的"去冗余"、"多维平滑"和"折叠"运算,使得新数据具备MIMO雷达自身和最小冗余阵列双重自由度扩展的特点。理论和仿真结果表明:该文算法能够有效估计出目标的4个参数值,且能够实现自动配对;在相同仿真条件下,该文算法的估计精度优于交替最小二乘和多维ESPRIT算法,并且提高了最大可估计的目标数目。

A new algorithm is proposed to estimate jointly the four parameters （EDOD, ADOD, EDOA, ADOA） of targets based on the double-extension of aperture degree of freedom by combining MIMO technique with Minimum redundancy array under the conditions of non-uniform rectangular array configurations both on transmitter and receiver. Firstly, the two permutation matrices are constructed by utilizing the operational properties of the Khatri-Rao product of multiple matrices. Then the new data which possesses the characteristics of the double-extension of degree of freedom is attained by performing the twice row permutating, the redundant items deleting, multi-dimensional smoothing and data folding operations on the received data. The results illustrate that： the proposed method can estimate the four parameters of targets efficiently, and the estimated parameters are paired automatically without extra pairing operation. The parameter estimation performance of the proposed method is better than those of the ALS and multi-dimension ESPRIT methods under the same simulation conditions. And the proposed method can provide much stronger parameter identifiability than the conventional ones.