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| 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) |
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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.
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Received: 04 March 2014
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Corresponding Authors:
Lu Hong-xi
E-mail: xdkd@163.com
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2015, Vol. 37 
