Robust adaptive radar beamforming based on iterative training sample selection using kurtosis of generalized inner product statistics  

作　　者：TIAN Jing ZHANG Wei 

机构地区：[1]School of Information and Electronics,Beijing Institute of Technology,Beijing 100081,China [2]National Key Laboratory of Electromagnetic Space Security,Chengdu 610036,China

出　　处：《Journal of Systems Engineering and Electronics》2024年第1期24-30,共7页系统工程与电子技术（英文版）

基　　金：supported by the National Natural Science Foundation of China(62371049)。

摘　　要：In engineering application,there is only one adaptive weights estimated by most of traditional early warning radars for adaptive interference suppression in a pulse reputation interval(PRI).Therefore,if the training samples used to calculate the weight vector does not contain the jamming,then the jamming cannot be removed by adaptive spatial filtering.If the weight vector is constantly updated in the range dimension,the training data may contain target echo signals,resulting in signal cancellation effect.To cope with the situation that the training samples are contaminated by target signal,an iterative training sample selection method based on non-homogeneous detector(NHD)is proposed in this paper for updating the weight vector in entire range dimension.The principle is presented,and the validity is proven by simulation results.

关 键 词：adaptive radar beamforming training sample selection non-homogeneous detector electronic jamming jamming suppression 

分 类 号：TN957.51[电子电信—信号与信息处理]