A Maximum A-Posteriori Probabilistic Approach using UAV-Nadir-Looking Wide-Band Radar for Remote Sensing Oil-Spill Detection

In this paper, we present a maximum a-posteriori probabilistic approach for oil spill detection at very low wind speeds using nadir-looking wide-band radar systems mounted on drones. Such platforms allow for to have radar measurements for calm ocean conditions when the winds' speed is very small challenging current state-of-the-art techniques used for oil spill detection. We study the detection accuracy by exploiting the variation in the distribution of radar power reflectivities from both C- and X-band for different oil thicknesses and electromagnetic wave frequencies. The joint probability density function (pdf)-based detector shows that by optimally combining reflectivity values evaluated at multiple scanning frequencies, the performance is boosted over the whole range of possible slick thicknesses. The probability of detection is further improved by running multiple scans of the scene.