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It is an important issue to study sea clutter suppression because it could interfere with the detection of targets above the sea surface severely. Spatial spectrum analyses show that the majority of sea clutter has low-frequency characteristics, compared to the high-frequency characteristics of the targets. This paper proposes a frequency-based spatial tracking filter to suppress sea clutter to facilitate targets identification. Experimental results show that the signal-to-clutter ratio can increase by more than 10 dB after filtering and the algorithm is feasible for practical use. In addition, the filtering equation can be optimized to maximize the signal-to-clutter ratio improvement. The equation parameters can also be adjusted to give a proper cut-off frequency for different targets and clutter.
It is an important issue to study sea clutter suppression because it could interfere with the detection of targets above the sea surface severely. Spatial spectrum analyzes that that majority of sea clutter has low-frequency characteristics, compared to the high-frequency characteristics of the This paper proposes a frequency-based spatial tracking filter to suppress sea clutter to facilitate targets identification. Experimental results show that signal-to-clutter ratio can increase by more than 10 dB after filtering and the algorithm is feasible for practical use. In addition, the filtering equation can be optimized to maximize the signal-to-clutter ratio improvement. The equation parameters can also be adjusted to give a proper cut-off frequency for different targets and clutter.