外辐射源雷达旋转阵列校正算法

Calibration algorithm using array rotation in passive radar

外辐射源雷达面临严重的多径干扰,但强多径信号也为阵列校正提供了优良的信号源,针对此提出了一种利用最强径信号的旋转阵列校正算法。该算法首先采用时域相关运算分离出最强径信号,然后通过旋转阵列来增加信号源和提供先验信息,接着利用比幅原理估计出阵列幅度误差,最后结合最大似然(maximum likelihood,ML)算法和最小二乘(least square,LS)算法估计出最强径信号到达角和阵列相位误差。分析了所提算法的适用条件,并推导了最强径信号到达角和阵列相位误差估计的克拉美-罗下界(Cramer-Rao lower bound,CRLB)。仿真和实测数据处理结果验证了该算法的有效性。

Passive radar usually encounters aggravated multipath interferences, which nonetheless provide effective signal sources for array calibration. A novel approach for array calibration in passive radar is proposed, exploiting the strongest multipath signal and array rotation. Firstly, the time-domain correlation between the surveillance and reference signals is employed to extract the strongest multipath signal. And then,the array ro- tation which provides both additional calibration sources and priori knowledge about the rotating angle is uti- lized. Following that, the estimation of the array amplitude mismatch by comparison on amplitudes, the direc- tion of arrival （DOA） of the strongest multipath signal and the array phase mismatch are finally estimated using the incorporation of maximum likelihood （ML） and least square （LS） algorithms. The applicable condition of the proposed approach is investigated, and the Cramer-Rao lower bound （CRLB） for DOA of the strongest multipath signal and the array phase mismatch is also derived. Numerical simulation and field data results dem- onstrate the behavior and effectiveness of the proposed algorithm.