General Four-Component Scattering Power Decomposition With Unitary Transformation of Coherency Matrix

被引:211
|
作者
Singh, Gulab [1 ]
Yamaguchi, Yoshio [1 ]
Park, Sang-Eun [1 ]
机构
[1] Niigata Univ, Grad Sch Sci & Technol, Niigata 9502181, Japan
来源
关键词
Polarimetric synthetic aperture radar (POLSAR); radar polarimetry; scattering power decomposition; MODEL;
D O I
10.1109/TGRS.2012.2212446
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
This paper presents a new general four-component scattering power decomposition method by implementing a set of unitary transformations for the polarimetric coherency matrix. There exist nine real independent observation parameters in the 3 x 3 coherency matrix with respect to the second-order statistics of polarimetric information. The proposed method accounts for all observation parameters in the new scheme. It is known that the existing four-component decomposition method reduces the number of observation parameters from nine to eight by rotation of the coherency matrix and that it accounts for six parameters out of eight, leaving two parameters (i.e., the real and imaginary parts of T-13 component) unaccounted for. By additional special unitary transformation to this rotated coherency matrix, it became possible to reduce the number of independent parameters from eight to seven. After the unitary transformation, the new four-component decomposition is carried out that accounts for all parameters in the coherency matrix, including the remaining T-13 component. Therefore, the proposed method makes use of full utilization of polarimetric information in the decomposition. The decomposition also employs an extended volume scattering model, which discriminates volume scattering between dipole and dihedral scattering structures caused by the cross-polarized HV component. It is found that the new method enhances the double-bounce scattering contributions over the urban areas compared with those of the existing four-component decomposition, resulting from the full utilization of polarimetric information, which requires highly improved acquisitions of the cross-polarized HV component above the noise floor.
引用
收藏
页码:3014 / 3022
页数:9
相关论文
共 50 条
  • [31] Model-based Scattering Power Decomposition with Superpixels for the Coherency Matrix
    Zhang, Shuang
    Wang, Lu
    Yu, Xiangchuan
    2019 IEEE INTERNATIONAL CONFERENCE ON ELECTRON DEVICES AND SOLID-STATE CIRCUITS (EDSSC), 2019,
  • [32] Evaluation of modified four-component scattering power decomposition method over highly rugged glaciated terrain
    Singh, Gulab
    Yamaguchi, Y.
    Park, S. -E.
    Avtar, Ram
    GEOCARTO INTERNATIONAL, 2012, 27 (02) : 139 - 151
  • [33] A four-component decomposition of POLSAR image
    Yamaguchi, Y
    Ishido, M
    Yamada, H
    Moriyama, T
    IGARSS 2005: IEEE International Geoscience and Remote Sensing Symposium, Vols 1-8, Proceedings, 2005, : 4073 - 4076
  • [34] Investigation on Unitary Piezoelectric Four-component Cutting Dynamometer
    Qu, G. J.
    Qian, M.
    Zhang, J.
    Xing, Q.
    ADVANCES IN MATERIALS MANUFACTURING SCIENCE AND TECHNOLOGY XIII, VOL 1: ADVANCED MANUFACTURING TECHNOLOGY AND EQUIPMENT, AND MANUFACTURING SYSTEMS AND AUTOMATION, 2009, 626-627 : 93 - 98
  • [35] An Improved Four-Component Decomposition with Distributed Double-Bounce Scattering Model
    Chen, Jiehong
    Zhang, Hong
    Wang, Chao
    PROCEEDINGS OF INTERNATIONAL CONFERENCE ON COMPUTER VISION IN REMOTE SENSING, 2012, : 344 - 349
  • [36] Modifying the Yamaguchi Four-Component Decomposition Scattering Powers Using a Stochastic Distance
    Bhattacharya, Avik
    Muhuri, Arnab
    De, Shaunak
    Manickam, Surendar
    Frery, Alejandro C.
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2015, 8 (07) : 3497 - 3506
  • [37] Comparison of Model-Based Four-Component Scattering Power Decompositions
    Yamaguchi, Yoshio
    Singh, Gulab
    Yi, Cui
    Park, Sang Eun
    Yamada, Hiroyoshi
    Sato, Ryoichi
    CONFERENCE PROCEEDINGS OF 2013 ASIA-PACIFIC CONFERENCE ON SYNTHETIC APERTURE RADAR (APSAR), 2013, : 92 - 95
  • [38] Four-component decomposition of sense making in algebra
    Palatnik, Alik
    Koichu, Boris
    PROCEEDINGS OF THE TENTH CONGRESS OF THE EUROPEAN SOCIETY FOR RESEARCH IN MATHEMATICS EDUCATION (CERME10), 2017, : 448 - 455
  • [39] ALTERNATIVE TO FOUR-COMPONENT DECOMPOSITION FOR POLARIMETRIC SAR
    Zhang, J. X.
    Huang, G. M.
    Wei, J. J.
    Zhao, Z.
    XXIII ISPRS CONGRESS, COMMISSION VII, 2016, 3 (07): : 207 - 211
  • [40] Darboux Transformation for a Four-Component KdV Equation
    Li, Nian-Hua
    Wu, Li-Hua
    COMMUNICATIONS IN THEORETICAL PHYSICS, 2016, 66 (04) : 374 - 378