Information fusion in underwater sonar simulation

Zhu, Y; Bull, M; Akin H.; Sepulveda, J; Rabelo, L

Keywords: systems, information, underwater, inference, networks, fusion, hypothesis, multiple, active, complexity, acoustics, fusions, passive, inferences, bayesian, methodologies, Computational, Geographical, engines, sonar, -, conditional, sonars, likelihoods, Dempster, Shafer, Multi-sensor

Abstract

This paper discusses information fusion methodologies, selection of one of these methodologies, and application of these fusion methodologies to underwater sonar simulation. Bayesian Inference and Dempster-Shafer are the two methods that have been studied in detail. In conclusion, the Dempster-Shafer approach was selected as the preferred method.Dempster-Shafer's main advantage is that it does not need conditional likelihoods. Also, Dempster- Shafer does not have computational complexity problems when multiple hypotheses and multiple conditional dependent events are examined. This method was applied to the multisensor information fusion problem in a simulation which includes a passive sonar, an active sonar, and a radar. The simulation is conducted on a geographical information system. © 2008 IEEE.

Más información

Título de la Revista: Proceedings - Winter Simulation Conference
Editorial: Society of Laparoendoscopic Surgeons
Fecha de publicación: 2008
Página de inicio: 1250
Página final: 1258
URL: http://www.scopus.com/inward/record.url?eid=2-s2.0-60749136325&partnerID=q2rCbXpz