Abstract
A new method based on chaos and neural network theory for small target detection in sea clutter is presented. The authors present the signal model. They then describe a neural network trained with the least-mean-square (LMS) algorithm for the dynamic reconstruction of sea clutter. A chaotic detection algorithm based on the neural network model is described. Some experimental results show that the new detection method operating with noncoherent radar data has a performance comparable with that of a standard Doppler CFAR processor.

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