Marine Environmental Impact on CFAR Ship Detection as Measured by Wave Age in SAR Images

Satellite synthetic aperture radar (SAR) images are recognized as one of the most efficient tools for day/night, all weather and large area monitoring ships at sea. However, false alarms discrimination is still key problem on SAR ship detection. While many techniques have been proposed treatment alarms, not enough emphasis has targeted to explore how obtained related changing ocean environmental conditions. To this end, we combined a set Sentinel-1 with surface wind wave data into dataset. were separated three distinct groups according age (WA) conditions present during image acquisition: young sea, old swell. A constant alarm rate (CFAR) detection algorithm was implemented based generalized gamma distribution (GΓD). Kolmogorov–Smirnov distance used analyze goodness-of-fit among environments. backscattering analysis different sizes targets sea clutter further performed using OpenSARShip automatic identification system (AIS) datasets assess its separability. We derived threshold adjustment WA showed efficacy drastically reduce alarms. our knowledge, use part CFAR novelty which could be tested evaluated sensors.