一种极化sar协方差矩阵综合四分量分解模型

an inte grated four-component model-based decomposition  of polarimetric sar with covariance matrix

  • 摘要: 基于多视协方差矩阵发展了一种综合选择性去取向和广义体散射的极化sar四分量分解模型 首先引入交叉极化相关系数进行螺旋体散射抑制和非反射对称地物去取向然后采用一种随hh和vv功率比值自适应变化的广义体散射模型来替代原体散射模型最后通过功率限制处理以完全消除分解负功率像素该处理不仅能够保持地物主导散射类型不变而且包含与krogager分解三分量对应的非相干分解 通过机载l波段esar和airsar极化数据实验并与其他分解模型的比较验证了该分解模型的有效性

     

    Abstract: in  this paper we developed a four-component model-based  incoherent  decomposition withcovariance matrix inte grating selective  de-orientation and generalized volume scattering.firstlyanew cross -polarization  coefficient  is  proposed which can be used  for  suppressing the helix scatteringand de-orientating the non-reflection  symmetric tar gets.secondl yyamaguchi  decomposition  is  im-proved  through adoptin g ageneralized volume scattering model instead  of  the ori ginal  one.the newvolume model can vary adaptivel y with the power ratio between hh and vv.lastlythe power constrain  is  utilized  to  eliminate  the negative  power completel y.the effectiveness  of  four-component decomposition  is  demonstrated lband e-sar and airsar polarimetric  data.the  results  suggest  thatcannot  onl y eliminate  the negative  phenomenon completel ybut also  can enhance double-bounce scattering in urban areas  remarkabl y.it can effectivel y suppress  the helix components which are  difficultto produce  in most natural  areas

     

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