基于逆高斯分布的复合高斯海杂波建模研究

摘要

复合高斯(CG)分布模型广泛应用于非高斯杂波建模，其纹理分量决定了杂波的非高斯特性。该文采用逆高斯分布的纹理分量建立了一种双参数复合高斯分布海杂波模型，即逆高斯-复合高斯(IG-CG)分布，并推导了其统计特性。同时，利用IPIX型雷达杂波数据进行拟合分析，结果表明该文建立的双参数IG-CG分布模型相对于单参数IG-CG分布模型和K分布模型，其残差平方和平均降低了30%和60%，能够更加准确地与实测数据相吻合。%The Compound-Gaussian (CG) distribution is widely used for modeling non-Gaussian clutter, as its texture component describes the non-Gaussian properties of the clutter. In this paper, a CG model with an inverse-Gaussian texture distribution, called the Inverse-Gaussian Compound-Gaussian (IG-CG) distribution, is proposed, and its distributional properties are derived. IPIX radar lake-clutter measurements have been analyzed, and the results show that the two-parameter IG-CG distribution model fits real radar data better than a single parameter IG-CG distribution model or a K distribution model.