Modelling and simulating SAR raw signals of oil-covered sea

Remote sensing has proved to be a powerful tool for studying ocean dynamics and detection of oil spills. In particular, synthetic aperture radar (SAR) systems have been shown to be very useful. The main effect of oil on the ocean surface consists of dampening the capillary waves: this reduces electromagnetic backscattering from areas where oil is present, generating darker zones in the SAR image. Dark areas in SAR images can be caused by several other phenomena, causing possible ambiguities in oil spill detection. A SAR raw signal simulator is a powerful tool for devising algorithms for oil slick detection. Besides, a good simulation can be an important step in identifying the nature of the slick. Modelling and simulation of SAR raw signals corresponding to a sea surface covered by an oil film are presented. The proposed SAR simulator is based on an ocean model and an oil slick model. Meaningful simulation experiments are presented and discussed, elucidating the role of pollutants, oil thickness, wind speed and direction, incident wavelength and angle and other radar parameters. Validation of the simulator is also presented by comparison with experimental data.