Advanced Sea Clutter Models and their Usefulness for Target Detection
Résumé
Robust naval target detection is of significant importance to national security, to navigation safety, and to environmental monitoring. Here we consider the particular case of high resolution coastal radars, working at low grazing angles. The robustness of detection heavily relies on the appropriate knowledge of two classes of backscattered signals: the target echo, and the sea echo. The latter, usually regarded as a noise, is known as the sea clutter. This particular combination, of high resolution and low grazing angles, raises considerable challenges to radar processing algorithms. Specifically, the probability density function governing the sea clutter amplitude is no more Gaussian and a lot of effort has been aimed at characterizing it. Three approaches are reviewed here: the stochastic, texture and chaotic models. While the stochastic models represent an essay to extend classical detection theory to radars operating in marine environment, the other two models represent entirely new paradigms. Since each model has its strengths and weaknesses and more testing on real data is required to credibly validate any of the proposed models, a definitive conclusion is far from reach. However, critical comments, as well as experimentally supported conclusions are presented in the paper.
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