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Robust adaptive radar beamforming based on iterative training sample selection using kurtosis of generalized inner product statistics
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作者 TIAN Jing ZHANG Wei 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2024年第1期24-30,共7页
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 s... 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. 展开更多
关键词 adaptive radar beamforming training sample selection non-homogeneous detector electronic jamming jamming suppression
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