基于极化敏感阵列抗有源干扰的测向算法

Direction-finding Algorithm Against Active InterferenceBased on Polarization-sensitive Array

摘要:

基于传统的极化敏感阵列多重信号分类(multiple signal classification,MUSIC)空间谱估计测向算法,提出了结合极化滤波与斜投影算子的极化域-空域二维联合空间谱估计超分辨测向算法。与传统极化MUSIC空间谱估计算法相比,所提算法根据接收到的混叠脉冲信号的时域、极化域特性,进行信号前沿段与叠加段的分段波达方向(direction of arrival,DOA)估计。在估计出前沿段信号极化域与空域参数后,以此对信号叠加段进行极化滤波与斜投影算子处理,更为准确地估计了目标雷达与诱饵的DOA。仿真实验结果表明,该算法可有效抑制诱饵信号的影响,提高目标雷达信号DOA 估计的准确度,实现多目标分辨。

Abstract:

On the basis of the traditional polarization-sensitive array multiple signalclassification (MUSIC) spatial spectrum estimation and direction-finding algorithm, a superresolutiondirection-finding algorithm was proposed, which combined polarization filteringand oblique projection operator for two-dimensional joint spatial spectrum estimation inpolarized domain and spatial domain. Compared with the traditional polarization MUSICalgorithm, the proposed algorithm performs direction of arrival (DOA) estimation ondifferent segments such as the leading edge segment and the superposition segment accordingto the time domain and polarization domain characteristics of the received pulse signal. Afterestimating the polarization domain and spatial domain parameters of the signal in the leadingedge segment, the polarization filtering and oblique projection operator are applied to thesignal in the superposition segment. The simulation results show that the algorithm cansuppress the influence of decoy signals effectively, improve the accuracy of DOA estimationof target radar signals, and achieve multi-target resolution.