Research Of Small Target Detection Within Sea Clutter Based On Chaos

In this paper, based on the prior knowledge of chaotic character of sea clutter, we discuss a method for detection of small target in sea clutter using neural network as a predictor. Neural network can capture the dynamics of strange attractor generating sea clutter. After the reconstruction of real-life Radar data, BP and RBF networks are regularized, and then a set of sample data from real-life data is inputted into the networks to train the neural networks respectively. As a sequence, according the nature of neural networks, these trained networks could approximate the model of dynamical system responsible for sea clutter. These networks can be used to detect small target within sea clutter as a predictor.