Four-Component Scattering Power Decomposition Algorithm with Rotation of Covariance Matrix Using ALOS-PALSAR Polarimetric Data

Remote Sensing

Mitsunobu Sugimoto¹  Kazuo Ouchi² 

[1] Department of Computer Science, School of Electrical and Computer Engineering, National Defense Academy, 1-10-20 Hashirimizu, Yokosuka, Kanagawa 239-8686, Japan;

关键词: polarimetric synthetic aperture radar (POLSAR);    scattering power decomposition;    radar polarimetry;    covariance matrix rotation;   

DOI  :  10.3390/rs4082199

来源: mdpi

【 摘 要 】

The present study introduces the four-component scattering power decomposition (4-CSPD) algorithm with rotation of covariance matrix, and presents an experimental proof of the equivalence between the 4-CSPD algorithms based on rotation of covariance matrix and coherency matrix. From a theoretical point of view, the 4-CSPD algorithms with rotation of the two matrices are identical. Although it seems obvious, no experimental evidence has yet been presented. In this paper, using polarimetric synthetic aperture radar (POLSAR) data acquired by Phased Array L-band SAR (PALSAR) on board of Advanced Land Observing Satellite (ALOS), an experimental proof is presented to show that both algorithms indeed produce identical results.

【 授权许可】

CC BY   
© 2012 by the authors; licensee MDPI, Basel, Switzerland.