The Research And Application Of Sea Clutter Suppression Processing Technology Based On Neural Network And Mathematical Morphology

The signal of sea clutter has a very strong correlation, especially manifested in the effect of sea spike. This correlation makes the traditional method of frequency-domain filtering based on power spectrum of sea clutter have not a so good suppressive effect. In order to suppress the sea clutter effectively, a method to suppress the sea clutter from the aspect of image processing is presented, which avoids the problem of sea clutter correlation emerged in traditional method. This method first makes use of image restoration technology to restore the ocean wave image obtained by the marine radar, and filters the noise in this ocean wave image to obtain the sea clutter image. And then it takes advantage of image segmentation technology to judge whether there is target in the sea clutter image. If does, separate them.The image restoration part presents image restoration technique based on neural networks and mathematical morphology. It inherits fitting character and convergence property of neural networks. Besides, it presents a new type of morphology amoeba structuring element to overcome the disadvantages of traditional filter methods and the noise of image has been smoothed effectively on the premise of keeping image edge information. Four types of improved image restoration technique are given, including one based on Hopfield neural network and mathematical morphology, one based on wavelet neural network and mathematical morphology, one based on transiently chaotic neural network and mathematical morphology, and one based on cellular neural network and mathematical morphology.The image segmentation part presents two new types of image segmentation technique and two improved ones based on neural networks, including one based on gray level information matrix method, which is obtained by minimizing the sum of distance values that is from every within-class gray level to central gray level, one based on gray level information matrix method, which is obtained by minimizing the sum of distance values that is from one within-class gray level to another, one based on Hopfield neural network, and one based on transiently chaotic neural network.In order to verify the method of sea clutter suppression presented from the angle of image processing, two groups of data that one group has a target and the other not, which is collected by the IPIX marine radar is used to conduct simulation experiment. The experiment results have been analyzed and compared carefully, which show this method can suppress sea clutter effectively.