基于Freeman分解的植被参数反演新方法
doi: 10.3724/SP.J.1146.2010.00763
A Novel Vegetation Parameters Inversion Method Based on the Freeman Decomposition
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摘要: 基于极化Freeman分解的极化协方差矩阵参数,极化干涉SAR互协方差矩阵可简化建模为植被高度、消光系数和地面干涉相位的函数。基于此,该文建立了以极化干涉SAR互协方差矩阵估算值与互协方差矩阵观测值之差为目标函数、以3个植被参数为未知量的优化模型,提出了基于Freeman分解的植被参数反演新方法。该方法避免了三阶段植被参数估计方法所面临的体相关系数确定问题,提供了一种独立于三阶段植被参数估计的新思路。仿真结果验证了新方法的有效性。Abstract: Based on the estimated polarimetric coherence matrices of the three different scattering mechanisms by Freeman decomposition, the polarimetric interferometric cross-coherence matrices could be simply modeled as a function of the vegetation height, the extinction coefficient and the topographic phase. Based on this model, a new optimization model is established. The target function of this new optimization model is the difference between the computed results of polarimetric interferometric cross-coherence matrices and their estimated results, the variables are the vegetation parameters. A new vegetation parameters inversion method based on the Freeman decomposition is proposed. Compared to three-stage inversion process, this new method does not need to estimate the volume correlation coefficient, so it could avoid the error of the estimation of the volume correlation coefficient and more importantly this new method supplies a new approach to the inversion of the vegetation height. The simulated PolInSAR data by the PolSARpro software is processed to validate the novel method.
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