极化方位角补偿信息支持下的植被参数反演
收稿日期: 2013-12-11
修回日期: 2014-04-11
网络出版日期: 2014-10-24
Forest Parameters Inversion with the Support of Compensation Information of Radar Polarization Orientation Angle
SAR图像中散射目标的散射矩阵受极化方位角(POA)的影响会改变散射体的散射特性，散射矩阵是极化干涉SAR (PolInSAR)估计不同极化状态下复相干性的基础。本文根据极化方位角产生机制，建立了多视情况下基于极化方位角补偿的极化干涉相干性估计模型，分析了极化方位角补偿对相干性估计方法和不同散射机制下相干性估计的影响程度，研究了基于三阶段法与极化方位角补偿的植被参数反演。利用L波段SIRC全极化SAR图像为实验数据验证极化方位角补偿对极化干涉相干性估计和植被参数反演的可行性。实验结果表明，极化方位角补偿能够改变不同极化状态相干性分布规律，提高相干直线拟合精度，改善植被参数反演的可靠性和合理性。
龙江平 丁晓利 汪长城 . 极化方位角补偿信息支持下的植被参数反演[J]. 测绘学报, 2014 , 43(10) : 1051 -1060 . DOI: 10.13485/j.cnki.11-2089.2014.0151
Polarization characteristics of scatterers are affected by the difference polarization orientation angle (POA), which influences the scattering matrix. Coherences with difference polarization states, which are important statistic data for Polarimetric SAR interferometry (PolInSAR) technology, are estimated by scattering matrix and applied to inversion of vegetation parameters using the coherence scatter model. Based on the generation mechanism of polarization orientation angle, the estimation model of complex coherence is constructed in view of compensation of polarization orientation angle. And then, complex coherences with difference estimation methods and difference scatter mechanisms are analyzed under the influence of compensation of polarization orientation angle. The relation between the compensation of polarization orientation angle and the forest parameters inversion is revealed by fitted coherence line with the model of there stage inversion. Using Quad-pol SIRC L -band SAR data, it is feasible for improvement the accuracy of complex coherence estimation and forest parameters inversion under the compensation of polarization orientation. The experiment results show that the distribution of difference polarization states can be changed with polarization orientation angle. With the compensation of polarization orientation angle, the accuracy of fitted coherence line is improved, and so the reliability and rationality of forest parameters inverted by three stage model can be improved.
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