Mathematical Techniques in Multisensor Data Fusion
Mathematical Techniques in Multisensor Data Fusion
Mathematical Techniques in Multisensor Data Fusion (Artech House Information Warfare Library)
Mathematical Techniques in Multisensor Data Fusion (Artech House Information Warfare Library)
Modeling the effectiveness of underwater sonar
Proceedings of the 38th conference on Winter simulation
Integration of underwater sonar simulation with a geographical information system
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Integrating simulation and geographic information system
Proceedings of the 2008 Spring simulation multiconference
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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.