Underlying topography and forest height estimation from SAR tomography based on a nonparametric spectrum estimation method with low sidelobes

作     者：Youjun Wang Xing Peng Qinghua Xie Xinwu Li Xiaomin Luo Yanan Du Bing Zhang 

作者机构：School of Geography and Information EngineeringChina University of Geosciences (Wuhan)WuhanPeople’s Republic of China Aerospace Information Research InstituteChinese Academy of SciencesBeijingPeople’s Republic of China School of Geographical SciencesGuangzhou UniversityGuangzhouPeople’s Republic of China School of GeomaticsLiaoning Technical UniversityFuxinPeople’s Republic of China 

出 版 物：《International Journal of Digital Earth》 (国际数字地球学报（英文）)

年 卷 期：2022年第15卷第1期

页      面：2184-2201页

核心收录：

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 0708[理学-地球物理学] 0835[工学-软件工程] 0704[理学-天文学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported in part by the National Natural Science Foundation of China[grant number 42101400],[grant number 42171387] in part by the Strategic Priority Research Program of the Chinese Academy of Sciences[grant number XDA19070202] 

主　　题：Underlying topography forest height TomoSAR G-Pisarenko method sidelobes 

摘      要：The underlying topography and forest height play an indispensable role in many fields,including geomorphology,civil engineering construction,forest investigation,and the modeling of natural *** a new microwave remote sensing technology with three-dimensional imaging capability,synthetic aperture radar(SAR)tomography(TomoSAR)has already been proven to be an important tool for underlying topography and forest height *** spectrum estimation methods have now been proposed for ***,most of the commonly used methods are susceptible to noise and inevitably produce sidelobes,resulting in a reduced accuracy for the inversion of forest structural *** this paper,to solve this problem,a nonparametric spectrum estimation method with low sidelobes-the G-Pisarenko method-is *** method performs a logarithmic operation on the covariance matrix to obtain the main scattering characteristics of the objects of interest while suppressing the noise as much as *** effectiveness of the proposed method is demonstrated by the use of both simulated data and P-band airborne SAR data from a tropical forest region in Gabon,*** results show that the proposed method can reduce the sidelobes and improve the estimation accuracy for the underlying topography and forest height.