Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 755-759 |
| Number of pages | 5 |
| Journal | IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences |
| Volume | E108.A |
| Issue number | 5 |
| DOIs | |
| State | Published - May 2025 |
| Externally published | Yes |
Keywords
- formation recognition
- high-frequency surface wave radar
- motion compensate
- robustness
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