In order to detect and identify oil-spilled on the sea by Airborne Laser-Induced Fluorescence, a fuzzy model and algorithm are put forward in this paper. The target to be detected on the sea may be one of the following: seawater, crude oil, diesel, lubricating oil, dirty water, sand, etc. The primary requirement for airborne sensors is to identify, in real-time, the substances targeted by the laser beam. There have been several algorithms developed for the detection of oil spilled on the sea by Airborne Laser-Induced Fluorescence, for example, the Pearson Correlation Coefficient method. The reason that we have decided to research the fuzzy model for the identification of oils spilled on the sea, is that there are some uncertainties and unknown differences between the “live” spectrum, and the substances targeted by the laser beam. The fuzzy algorithm presented in this paper is based on a fuzzy closeness matrix. All values in the matrix are calculated from the spectrum of a target and the spectra of the above mentioned “pure” substances.
This paper outlines the fuzzy model for the identification of the spilled oils, and makes a comparison with the Pearson Correlation Coefficient method in an effort to increase the level of confidence in the identification results and reduce the computational time. The results of ground tests using known targets show an increased confidence with the identification results using the Fuzzy Model when compared to the results of the Pearson Correlation Coefficient Algorithm.