Synthetic Aperture Radar (SAR) has over the years evolved to be one of the most promising remote sensing modalities for large-scale monitoring of the ocean and maritime activity. The use of SAR imagery in a variety of monitoring applications has motivated significant research on the statistical modelling of such images, with recent work focusing on the ability of the data’s heavy-tailed nature to be accurately modelled using distributions such as the a-stable and the Generalised Rayleigh distribution. Certain SAR applications, such as the detection of ships at sea have however as of yet not benefited from the use of these newly proposed statistical models. In this paper we present a Cauchy-Rayleigh Constant False Alarm Rate (CFAR) detector for the detection of ships at sea, showing that it can achieve superior performance to other previously used variants such as Weibull CFAR. We demonstrate the performance of our detector on high resolution TerraSAR-X data.
|Title of host publication||XXVIème Colloque GRETSI 2017|
|Subtitle of host publication||Juan-Les-Pins, 5-8 Septembre 2017|
|Publication status||Published - 5 Sep 2017|