摘要
利用极化干涉合成孔径雷达(Polarimetric Interferometry SAR,PolInSAR)数据反演森林参数问题为当前PolInSAR研究的热点问题。经典的森林参数反演算法是基于随机散射体模型(Random Volume over Ground,RVoG)的阶段反演算法,该算法中直线拟合误差和体散射估计误差会严重影响反演精度。为了提高树高估计精度,该文使用整体最小二乘法直线拟合得到更精确的地表相位估计结果,并提出以Gamma函数为线性度量自适应地估计体散射去相干,得到了改进的PolInSAR三阶段反演算法,实验结果表明改进算法可靠有效。
Employing Polarimetric Interferometry Synthetic Aperture Radar （PolInSAR） data to inverse forest parameters is a hot topic in the research field of PolInSAR. The typical forest parameter inversion algorithm is the three-stage inversion algorithm based on Random Volume over Ground （RVoG） model. The errors of linear fitting and volume scattering correlation estimation are the major factors for parameter estimation accuracy. In this paper, straight line fitting employing the total least squares method is used to estimate the ground phase. Then, the Gamma function is applied as the line measure to adaptively estimate the volume scattering correlation. The improved three-stage inversion algorithm with PolInSAR is presented. The experiment result proves the forest parameters inversion result is accurate and reliable.
出处
《雷达学报（中英文）》
CSCD
2014年第1期28-34,共7页
Journal of Radars
基金
国家自然科学基金(61072113)资助课题
