Publication Date:
2015-08-11
Description:
Several detection statistics have been proposed for detecting fine ground disturbances between two synthetic aperture radar (SAR) images, such as vehicle tracks. The standard method involves estimating a local correlation coefficient between images. Other methods have been proposed using various statistical hypothesis tests. One of these alternative methods is a generalized likelihood ratio test (GLRT), which compares a full-correlation image model to a no-correlation image model. In this letter, we expand the GLRT to polarimetric SAR data and derive the appropriate GLRT detection statistics. Additionally, we explore relaxing the equal variance/equal polarimetric covariance assumptions used in previous results and find improved performance on macroscopic scene changes.
Print ISSN:
1545-598X
Electronic ISSN:
1558-0571
Topics:
Architecture, Civil Engineering, Surveying
,
Geography
,
Geosciences
