刘玉等：Bistatic Coherent Polarimetric Scattering of Randomly Corrugated Layered Snow Surfaces

Bistatic Coherent Polarimetric Scattering of Randomly Corrugated Layered Snow Surfaces 

作者:Liu, Y (Liu, Yu)[ 1 ] ; Chen, KS (Chen, Kun-Shan)[ 2,3 ] ; Xu, P (Xu, Peng)[ 1 ] ; Li, ZL (Li, Zhao-Liang)[ 3 ]  

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 

页: 4721-4739 

特刊: SI 

DOI: 10.1109/JSTARS.2017.2701147 

出版年: NOV 2017 

摘要

We analyzed the bistatic coherent scattering mechanism of a layered randomly corrugated snow surface, a typical rough surface, with radar polarimetry theory whose scattering matrix was obtained from a physical-based full wave numerical simulation by solving Maxwell's equations. The effects of top-bottom structure, layer thickness, frequency response, and angular dependence are illustrated by observing stokes vector, coherence matrix, and Kennaugh matrix. The results show that top-bottom structure and snow thickness change the state of polarization depending on frequency and bistatic configuration. Analyzing the bistatic polarimetric scattering mechanism based on numerical simulation and the polarimetry theory can be an efficacious source for configuring bistatic observation to detect and classify radar targets. For example, observation at a specular angle of 55 degrees comparatively contains more information on surface structure, and wave entropy is more preferable over degree of polarization as a snow surface structure estimator. Moreover, parameters from Kennaugh decomposition can indicate top-bottom structure better than layer thickness. Last but not the least, we also found that the symmetry assumption commonly used in classical theory of polarization is generally not valid for bistatic observation, and the combination of some Huynen parameters can be reasonably good indicators of snow surface structural symmetry. We expect this paper to offer deeper understanding of the coherent imaging of snow surfaces and to help design a novel bistatic imaging system for layered snow surface.

通讯作者地址: Chen, KS (通讯作者)

 Chinese Acad Agr Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China.

 Chinese Acad Agr Sci, Key Lab Agri Informat, Minist Agr, Inst Agr Resources & Reg Planning, Beijing 100101, Peoples R China.

 [ 1 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China