极化自适应滤波算法的新实现  

A New Method of Realization of Adaptive Filtering in Polarization Domain

作　　者：乔晓林[1] 薛敬宏[1] 邵仙鹤[1] 

机构地区：[1]哈尔滨工业大学信息技术研究所,山东威海264209

出　　处：《现代雷达》2006年第1期58-60,共3页Modern Radar

摘　　要：当目标信号与杂波干扰信号在时域、频域和空域的状态特征难以区分时,若两者在极化域可分,则可利用极化信息进行雷达目标检测。由于在强杂波的情况下信干比比较小,而且干扰的极化状态通常是未知的,或随时间或空间是不断变化的,传统的极化滤波算法并不能满足要求。文中针对强杂波环境下,提出了一种极化域新的自适应滤波算法,该方法基于线性约束最小方差(LCMV)准则,采用变极化接收技术,实现对信号的最佳接收,为实现实时处理和自适应快速变化的干扰,推导了一种递推极化滤波算法,为实现实时跟踪提供了一种可能,仿真结果也证明了该方法的有效性。In addition to the information associated with the time, frequency and spatial domains, the information in polarization domain should also be used to improve the detection capability of radar systems. The traditional methods of polarization filtering are not suitable for the detection of targets in an environment containing strong jamming because the signal/jamming ratio is usually every low and the polarization state of the jamming is unknown or distributed. In this paper, specificallym for the strong jamming environment, a new adaptive filtering algorithm in polarization domain using criterion of Linear Constraint Minimum Variance （LCMV） is proposed. The signal is optimized according to the variable polarization of antenna, For the realization of algorithm and the adaption to the fast varying interference, a recursion polarization filtering algorithm is derived which can adapt to the polarization states of the jamming at sampling speed. Simulations show the valiclity of that method.

关 键 词：自适应滤波 极化 线性约束最小方差 

分 类 号：TN957.51[电子电信—信号与信息处理]