Unstructured Versus Structured GLRT for Multipolarization SAR Change Detection
Open Access
- 27 April 2015
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Geoscience and Remote Sensing Letters
- Vol. 12 (8) , 1665-1669
Abstract
Coherent multipolarization synthetic aperture radar (SAR) change detection exploiting data collected from N multiple polarimetric channels is addressed in this letter. The problem is formulated as a binary hypothesis testing problem, and a special block-diagonal structure for the polarimetric covariance matrix is forced to design a detector based on the generalized likelihood ratio test (GLRT) criterion. It is shown that the structured decision rule ensures the constant false alarm rate property with respect to the unknown disturbance covariance. Results on both simulated and real high-resolution SAR data show the effectiveness of the considered decision rule and its superiority against the traditional unstructured GLRT in some scenarios of practical interest.Keywords
Funding Information
- Engineering and Physical Sciences Research Council (EPSRC) (EP/K014307/1)
- MOD University Defence Research Collaboration in Signal Processing and the University of Naples “Federico II”
This publication has 9 references indexed in Scilit:
- Invariant Rules for Multipolarization SAR Change DetectionIEEE Transactions on Geoscience and Remote Sensing, 2014
- Unsupervised Change Detection in Multitemporal SAR Images Over Large Urban AreasIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014
- Change detection and classification of multi-temporal SAR series based on generalized likelihood ratio comparing-and-recognizing2014
- Generalized CFAR Property and UMP Invariance for Adaptive Signal DetectionIEEE Transactions on Signal Processing, 2013
- A test statistic in the complex wishart distribution and its application to change detection in polarimetric SAR dataIEEE Transactions on Geoscience and Remote Sensing, 2003
- Coregistration of interferometric SAR images using spectral diversityIEEE Transactions on Geoscience and Remote Sensing, 2000
- Coherence estimation for SAR imageryIEEE Transactions on Geoscience and Remote Sensing, 1999
- Optimal speckle reduction in polarimetric SAR imageryIEEE Transactions on Aerospace and Electronic Systems, 1990
- Distributions of Matrix Variates and Latent Roots Derived from Normal SamplesThe Annals of Mathematical Statistics, 1964