False Plot Identification Using Multi-frame Clustering for Compact HFSWR

Compact high-frequency surface wave radar suffers from a high false alarm rate in target detection due to its low transmit power and wide beam, thus a large number of false plots are produced, which increases the computational burden of subsequent target tracking algorithm and easily leads to producing false tracks. In this paper, a two-stage false plot identification method is proposed. Firstly, a multi-frame plot clustering algorithm is proposed to cluster the potential plots of the same target in several consecutive frames, the plots outside the clusters are removed as false plots. Then, the differences in terms of range and Doppler velocity between the plot in the center frame and those in its neighbor frames in each cluster are used as features. Finally, a trained extreme learning machine is applied to the obtained features to recognize the remaining false plots. Experimental results with both simulated and field data demonstrate the effectiveness of the proposed method for false plot identification.