Adaptive Radar Target Detection Based On Inverse Gaussian And Generalized Gaussian Texture Distribution

Target detection is widely used in daily life,military and scientific research.Target detection under sea clutter is a hot research field for domestic and international experts.However,with the continuous application of high resolution radar in target detection system,the sea clutter is nonGaussian and non-stationary,and brings serious tail.Therefore,how to model sea clutter and how to choose detection algorithm are very important.The adaptive radar detection algorithm are studied for point targets in this thesis.In order to solve the serious problem of trailing sea clutter of high resolution radar,we use the compound Gaussian distribution to accurately fit the sea clutter.Aiming at the performance loss caused by the traditional target detector neglecting the effect of texture on the covariance matrix estimation,We propose MMSE algorithm and MAP algorithm to accurately estimate the covariance matrix,and applies them to the detector whose texture follows inverse Gaussian distribution.In order to verify the performance of the detector satisfying the compound Gaussian distribution,we propose a generalized Gaussian distribution detector.The main work of this paper is summarized as follows.In the first part,we introduce the detection background of radar surface targets,and summarize the development of target detector.In the second part,we summarize the basic physical characteristics of sea clutter,analyze the advantages and disadvantages of various distributions and appropriate modeling models on the basis of current radar detection techniques,and finally introduce several common detection algorithms and analyzes them.In the third part,we first introduce the inverse Gaussian texture in sea clutter,then deduce two covariance matrix estimation algorithms by the MMSE estimate and the MAP estimate,and apply the MMSE and MAP estimates to the inverse Gaussian texture,we obtain the MMSE-IGD-GLRT and MAP-IGD-GLRT.At last,comparing with other detectors,the MMSE-IGD-GLRT and MAP-IGDGLRT have a better detection performance in the experiments.In the fourth part,a new detector,that is NSCM-GGD-GLRT,is proposed,where the texture satisfied the GGD,and the detection performance of NSCM-GGD-GLRT is verified by experiments,superior to the compared ones.In the fifth part,we generalize the whole text,and come up with some ideas to make this paper better.