Systems Engineering and Electronics ›› 2024, Vol. 46 ›› Issue (2): 419-427.doi: 10.12305/j.issn.1001-506X.2024.02.06

• Electronic Technology • Previous Articles    

A false plot identification method based on multi-frame clustering for compact HFSWR

Weifeng SUN, Linlin ZHAO, Yonggang JI, Yongshou DAI   

  1. College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao 266580, China
  • Received:2022-12-02 Online:2024-01-25 Published:2024-02-06
  • Contact: Weifeng SUN

Abstract:

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%.

Key words: compact high-frequency surface wave radar (HFSWR), false plot identification, multi-frame clustering, extreme learning machine

CLC Number: 

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