Multi-ship Formation Recognition for HFSWR in a Long Coherent Integration Time

The deep learning method has been proven to be perfect in the field of multi-ship formation (MSF) recognition for high-frequency surface wave radar (HFSWR). However, the range-Doppler (RD) images of MSF are not always available in large quantities for training. And there is diversification in formation styles. In this paper, we propose a signal processing method for HFSWR formation recognition, which performs RD imaging through coherent accumulation and motion compensation. In the Doppler profile, the peaks are equal to sub-targets. The experiments based on actual RD background verify the feasibility and robustness of the proposed method.