混合Gamma拖尾Rayleigh分布的高分辨SAR图像建模

发布时间：2018-02-02 03:46

本文关键词： 合成孔径雷达图像乘积模型拖尾Rayleigh分布混合Gamma分布 Mellin变换　出处：《测绘学报》2014年02期 　论文类型：期刊论文

【摘要】：提出一种基于乘积模型的统计模型,称为混合Gamma拖尾Rayleigh分布模型。在该模型中,利用拖尾Rayleigh分布对相干斑进行建模,使模型可以精确地拟合高分辨率合成孔径雷达SAR图像相干斑的尖峰和拖尾的特征;同时引入混合Gamma分布对高分辨SAR图像雷达散射截面积(radar cross section,RCS)复杂起伏特性进行表征。基于Mellin变换,推导出混合Gamma拖尾Rayleigh分布对数累计量参数估计公式,提高了参数估计精度,从而实现了对高分辨率合成孔径雷达SAR图像的精确建模。最后通过真实SAR图像对本文提出的模型与已有模型进行比较。试验结果表明,本文提出的模型能够对不同的高分辨率合成孔径雷达SAR图像进行统计建模,并且具有较高的拟合精度。
[Abstract]:A statistical model based on product model is proposed, which is called mixed Gamma trailing Rayleigh distribution model. In this model, the speckle is modeled by trailing Rayleigh distribution. The model can accurately fit the peak and tail characteristics of speckle in high resolution synthetic aperture radar (SAR) images. At the same time, the mixed Gamma distribution is introduced to the radar cross section area of high-resolution SAR images. Based on Mellin transform, the parameter estimation formula of logarithmic cumulant of mixed Gamma trailing Rayleigh distribution is derived, which improves the precision of parameter estimation. Thus, the precise modeling of high-resolution synthetic aperture radar (SAR) images is realized. Finally, the model proposed in this paper is compared with the existing models through real SAR images. The experimental results show that. The proposed model can be used for statistical modeling of different high resolution synthetic aperture radar (SAR) images and has high fitting accuracy.
【作者单位】：南京理工大学电光学院;
【基金】：总装备部预研部基金(9140A13030211BQ02) 教育部博士点基金(20113219110018) 南京理工大学研究基金(2010ZDJH05;2011ZDJH13) 江苏省创新计划(CXLX11_0252)
【分类号】：P225.1;TN957.52
【正文快照】： 1引言SAR图像统计建模是SAR图像研究的重要内容,它旨在通过统计的方法描述SAR图像数据,以解释SAR图像的统计特性[1-2]。SAR图像统计特性不仅有助于深入了解地物的散射机理,而且合理的SAR图像统计特性可以有效地提高SAR图像相干斑抑制、分割,RCS重构以及目标检测和识别能力[3-5

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