A false plot identification method based on multi-frame clustering for compact HFSWR
Compact high-frequency surface wave radar(HFSWR)has low signal-to-noise ratio and high false alarm rate in target detection due to its low transmit power,a large number of false plots will be produced,which degrades the target tracking performance.In order to remove the false plots,a two-stage cascaded false plot identification method including multi-frame clustering module and extreme learning machine based classification module is proposed with target motion characteristics well explored.Firstly,the multi-frame plot clustering method based on optimal neighborhood size is utilized to cluster the potential plots belonging to the same target with the plot to be identified in consecutive multiple frames.Then,the differences in terms of range-Doppler velocity between the plot to be identified and plots in its neighbor frames are calculated as features,and the extreme learning machine is applied to these features to identify the false plots.Experimental results demonstrate that the proposed method can cluster the plots belonging to the same target accurately,and achieves a false plot identification rate of 95％.
万方数据
维普
