多径环境下的密集假目标干扰抑制技术研究

Dense False Target Jamming Suppression in Multipath Environment

密集假目标干扰兼具欺骗和压制的干扰效果,是对抗现代相参雷达的典型干扰.对于地面雷达,当干扰机位于低仰角复杂环境时,其接收到的干扰信号可能存在多径效应,导致传统的副瓣对消(SLC)算法性能明显恶化.针对该问题,提出一种基于多径筛选的并行SLC算法.算法在假目标检测的基础上,通过K-Means无监督聚类对各假目标峰值的通道间相位矢量进行聚类分析;根据聚类结果筛选各路径的干扰样本进行并行SLC处理;针对各路对消结果进行同距离选小,从而实现多径环境下的密集假目标干扰抑制.利用某型雷达采集的实测数据验证了算法的有效性.

Dense false target jamming is a typical jamming against modern coherent radar,possessing both deception and suppression jamming effects.For ground-based radars,when countering the jammer with a low elevation angle in a complex environment,the received signals may suffer from multipath effects,resulting in a significant deterioration of the performance of the traditional side lobe cancellation(SLC)algorithm.Aiming at this problem,a parallel SLC algorithm was proposed based on multipath samples clustering.Based on false target detection,the algorithm was arranged firstly to perform unsupervised clustering with K-means algorithm for the multi-channel-phase vector of each peak.Secondly,the jamming samples of each path were picked for SLC processing.Finally,the minimum value of the same range bin of all the paths was selected,so as to realize the dense false target jamming suppression in the multipath environment.The effectiveness of the algorithm was verified according to the filed data gathered from a kind of radar.