Bayesian Statistics of Wide-Band Radar Reflections for Oil Spill Detection on Rough Ocean Surface
AbstractIn this paper, we present a probabilistic approach which uses nadir-looking wide-band radar to detect oil spills on rough ocean surface. The proposed approach combines a single-layer scattering model with Bayesian statistics to evaluate the probability of detection of oil slicks, within a plausible range of thicknesses, on seawater. The difference between several derived detection algorithms is defined in terms of the number of frequencies used (within C-to-X-band ranges), as well as of the number of radar observations. Performance analysis of all three types of detectors (single-, dual- and tri-frequency) is done under different surface-roughness scenarios. Results show that the probability of detecting an oil slick with a given thickness is sensitive to the radar frequency. Multi-frequency detectors prove their ability to overcome the performance of the single- and dual-frequency detectors. Higher probability of detection is obtained when using multiple observations. The roughness of the ocean surface leads to a loss in the reflectivity values, and therefore decreases the performance of the detectors. A possible way to make use of the drone systems in the contingency planning is also presented. View Full-Text
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Hammoud, B.; Ndagijimana, F.; Faour, G.; Ayad, H.; Jomaah, J. Bayesian Statistics of Wide-Band Radar Reflections for Oil Spill Detection on Rough Ocean Surface. J. Mar. Sci. Eng. 2019, 7, 12.
Hammoud B, Ndagijimana F, Faour G, Ayad H, Jomaah J. Bayesian Statistics of Wide-Band Radar Reflections for Oil Spill Detection on Rough Ocean Surface. Journal of Marine Science and Engineering. 2019; 7(1):12.Chicago/Turabian Style
Hammoud, Bilal; Ndagijimana, Fabien; Faour, Ghaleb; Ayad, Hussam; Jomaah, Jalal. 2019. "Bayesian Statistics of Wide-Band Radar Reflections for Oil Spill Detection on Rough Ocean Surface." J. Mar. Sci. Eng. 7, no. 1: 12.
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