Performance Analysis of Detector Algorithms Using Drone-Based Radar Systems for Oil Spill Detection

Abstract

In this paper, we develop algorithms for oil spill detection using radar remote sensing. The algorithms take into account both the mathematical and the physical modeling of the sea surface covered by oil slicks. We use the statistical characterization of the power reflectivity and its distribution under various oil thicknesses and electromagnetic wave frequencies. We first introduce a single frequency (SF) oil spill detector that uses single or multiple observations (SO or MO) of power reflection coefficients over several scanning iterations for the sea area. Then, using Monte Carlo simulations we address the correctness of this detector by choosing different frequencies. Results show the inability of this detector to effectively distinguish between oil slicks and oil-free slicks for the total range of possible thicknesses. Nevertheless, increasing the number of observations leads to an increase in the effectiveness of the detector. An upgrade of this detector is the dual-frequency (DF) detector using single and multiple observations where two electromagnetic frequencies are used at the same time. Performance analysis of this detector proves its ability to overcome the drawbacks of the first detector by providing accurate detection especially for multiple observations.