Single point and spatial statistics of polarimetric SAR imagery

A prerequisite for the design of any target detection scheme is an understanding of the clutter environment against which targets are to be detected. For polarimetric synthetic aperture radar (SAR) imagery, statistical models for homogeneous clutter based on both multi-variate Gaussian distributions and multi-variate K distributions have been extensively investigated. The first aim of this paper is to investigate the extent to which such models can be used to represent genuine polarimetric SAR clutter. To this end, the models have been tested on imagery obtained using a C-band airborne polarimetric SAR system, which is described. The validity of the Gaussian model as a description of the clutter statistics of a particular extended region is discussed. However, not all clutter regions can be represented by the simple Gaussian speckle model as is demonstrated in the case where the validity of using low order K distributions to describe woodland clutter is assessed. A point of particular interest is whether, when a low order K distribution description is most appropriate, the order parameters are significantly different between polarimetric channels. Suitable statistical tests have been used to address this question as described. The second aim is to investigate the spatial statistics of polarimetric SAR imagery using data provided by the C-band system. The measurement of correlation shapes and lengths and their use to determine whether there is significant variation in correlation properties is also discussed