Multiscale modelling for target detection in complex synthetic aperture radar imagery

Multiscale models can be used to capture the scale dependent behaviour of the statistics in radar imagery. This behaviour is expected to be different for different types of natural background, and for different objects of interest such as vehicles. We demonstrate that discrimination between two types of natural background in SAR imagery is possible using multiscale autoregressive and multiscale autoregressive moving average models. This result can be exploited in adaptive algorithms for automated target detection.