基于特征空间的极化敏感阵列滤波分析

Analysis on Eigenspace-Based Polarization Sensitive Array Filtering

为了提高极化敏感阵列的滤波性能,提出将基于特征空间的滤波方法和多线性约束最小方差波束形成准则联合应用到极化敏感阵列滤波中。首先给出了系统模型,然后介绍了基于特征空间的滤波方法,并进一步分别讨论了存在导数约束和零点约束的条件下不同的滤波方法,在此基础上对比分析了不同条件下的滤波性能。计算机仿真结果表明,文中方法具有比传统极化敏感阵列滤波更高的输出信干噪比,具有对阵列指向误差不敏感的特性,而且可以灵活地选择保存或不保存约束,同时也优于传统标量阵列的滤波性能。

In order to improve the filtering performance of the polarization sensitive array,the combina-tion of eigenspace-based array filtering method and linearly constrained minimum variance beamformer is put forward.The system model and basic idea of the algorithm are given,and then the filtering methods are dis-cussed under derivation constraints and zero constraints,respectively.Computer simulation results show that the proposed method can effectively improve the output SINR（signal to interference and noise ratio）and the linear constraints can be treated flexibly.At the same time it is not sensitive to the array pointing errors and outperforms the performance of traditional scalar array.