双基地MIMO雷达多目标定位及互耦参数估计

Multi-target localization and estimation of mutual coupling bistatic MIMO radars

针对MIMO雷达收发阵元间存在互耦会严重影响目标定位算法性能的情况,提出一种双基地MIMO雷达多目标定位及互耦参数估计的算法.利用均匀线阵互耦矩阵的特点和MIMO雷达的特性获得满足ESPRIT算法的信号子空间,在不需要任何互耦矩阵信息情况下采用ESPRIT算法实现了目标角度估计,且估计出的角度参数自动配对.根据所估计的目标方位角度,利用信号子空间和联合导向矩阵之间的关系,将MIMO雷达的互耦参数估计转化为线性约束二次最小化问题,估计出互耦系数矩阵,实现了MIMO雷达的自校正.该方法的优点是避免了多维空间谱搜索带来的庞大计算量和迭代中的全局收敛性问题,同时得到了收、发阵列互耦参数估计的闭式解.仿真结果表明算法估计性能接近于互耦已知时二维MUSIC算法.

Owing to mutual coupling in the transmitter and arriver arrays,the performance of localization algorithm is seriously degraded,thus,a method for joint estimation of angle and mutual coupling for bistatic multiple-input multiple-output（MIMO）radar was presented.A signal subspace satisfied ESPRIT（estimations signal parameter via rotational invariance techniques）algorithm could be obtained by using the mutual coupling matrix of uniform linear array and the structural specialty of MIMO radar.The direction of departure（DOD）and direction of arrival（DOA）were estimated by ESPRIT without the knowledge of mutual coupling parameters.According to the angle estimation of targets,the estimation of mutual coupling was turned into linear constrained quadratic minimization problem by using the relationship between signal subspace and steering matrix,and then the mutual coupling matrix was achieved for self-calibration of bistatic MIMO radar.The strongpoint is that the proposed method avoids multi-dimensional search and global convergence problem due to iterative,and the estimation of mutual coupling is solved in closed form.Simulation results demonstrate that the performance of proposed method is closed to 2-D MUSIC（multiple signal classification）algorithm.