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Target detection based on eigen-decomposition using PolInSAR data

  • Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, an eigenvalue decomposition method of the simplified polarimetric interferometric coherency matrix (SPICM) is proposed for polarimetric SAR interferometry (PolInSAR) data analysis. Firstly, the definition of the SPICM is given. Then, the characteristics of this matrix are analyzed and connected with the polarimetric scattering mechanism of targets and clutter objects. Further more the eigenvalue decomposition method is described in detail. The polarimetric scattering vectors can be converted to optimal states, in which the optimal coherence between the signals in same polarimetric states of two antennas can be obtained. Finally, the method is verified with E-SAR data. The results show that the proposed method is promising in classification or recognition of man-made targets such as buildings.

Original languageEnglish
Title of host publicationRadarCon'11 - In the Eye of the Storm
Subtitle of host publication2011 IEEE Radar Conference
Pages654-657
Number of pages4
DOIs
StatePublished - 2011
Event2011 IEEE Radar Conference: In the Eye of the Storm, RadarCon'11 - Kansas City, MO, United States
Duration: 23 May 201127 May 2011

Publication series

NameIEEE National Radar Conference - Proceedings
ISSN (Print)1097-5659

Conference

Conference2011 IEEE Radar Conference: In the Eye of the Storm, RadarCon'11
Country/TerritoryUnited States
CityKansas City, MO
Period23/05/1127/05/11

Keywords

  • Coherence optimization
  • Eigenvalue Decomposition
  • Polarimetric SAR Interferometry (PolInSAR)
  • Simplified Polarimetric Interferometric Coherency Matrix (SPICM)

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