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Jinfeng HU Huanrui ZHU Huiyong LI Julan XIE Jun LI Sen ZHONG
Recently, many neural networks have been proposed for radar sea clutter suppression. However, they have poor performance under the condition of low signal to interference plus noise ratio (SINR). In this letter, we put forward a novel method to detect a small target embedded in sea clutter based on an optimal filter. The proposed method keeps the energy in the frequency cell under test (FCUT) invariant, at the same time, it minimizes other frequency signals. Finally, detect target by judging the output SINR of every frequency cell. Compared with the neural networks, the algorithm proposed can detect under lower SINR. Using real-life radar data, we show that our method can detect the target effectively when the SINR is higher than -39dB which is 23dB lower than that needed by the neural networks.