Forest Parameters Inversion Based on Nonstationarity Compensation and Mapping Space Regularization
Lu Hong-xi① Song Wen-qing① Li Fei① Wang Ying-hua① Liu Hong-wei① Bao Zheng① Huang Hai-feng②
①(National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China) ②(College of Electronic Science and Engineering, National University of Defense Technology, Changsha 430074, China)
Abstract：Forest parameters inversion is an important application of Polarimetric Interference Synthetic Aperture Radar (PolInSAR). The traditional inversion method does not take into account the amplitude and phase non-stationary of observation, and its non-uniform distribution effect on the estimation of the principal linear change direction. Aiming at these problems, an amplitude and phase calibration approach is proposed to compensate the polarization coherence matrix nonstationarity, to enhance the performance of complex coherences estimation. Moreover, this paper develops a Mapping Space Regularization (MSR) technology which promises to be able to eliminate the non-uniform distribution effect of sample coherences on the linear variation of complex coherences. Based on MSR, the Principal Component Analysis (PCA) is further introduced to the linear variation model extraction. Processing results of ESA PolSARpro simulated data verify the better robustness and estimation accuracy of the proposal in forest parameters inversion.
卢红喜, 宋文青, 李飞, 王英华, 刘宏伟, 保铮, 黄海风. 基于幅相一致性校正的稳健植被参数反演方法[J]. 电子与信息学报, 2015, 37(2): 283-290.
Lu Hong-Xi, Song Wen-Qing, Li Fei, Wang Ying-Hua, Liu Hong-Wei, Bao Zheng, Huang Hai-Feng. Forest Parameters Inversion Based on Nonstationarity Compensation and Mapping Space Regularization. , 2015, 37(2): 283-290.
2015, Vol. 37 
