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20 March 1998 Non-ad-hoc decision rule for the Dempster-Shafer method of evidential reasoning
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Abstract
This paper is concerned with the fusion of identity information through the use of statistical analysis rooted in Dempster-Shafer theory of evidence to provide automatic identification aboard a platform. An identity information process for a baseline Multi-Source Data Fusion (MSDF) system is defined. The MSDF system is applied to information sources which include a number of radars, IFF systems, an ESM system, and a remote track source. We use a comprehensive Platform Data Base (PDB) containing all the possible identity values that the potential target may take, and we use the fuzzy logic strategies which enable the fusion of subjective attribute information from sensor and the PDB to make the derivation of target identity more quickly, more precisely, and with statistically quantifiable measures of confidence. The conventional Dempster-Shafer lacks a formal basis upon which decision can be made in the face of ambiguity. We define a non-ad hoc decision rule based on the expected utility interval for pruning the `unessential' propositions which would otherwise overload the real-time data fusion systems. An example has been selected to demonstrate the implementation of our modified Dempster-Shafer method of evidential reasoning.
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Ali Cheaito, Michael Lecours, and Eloi Bosse "Non-ad-hoc decision rule for the Dempster-Shafer method of evidential reasoning", Proc. SPIE 3376, Sensor Fusion: Architectures, Algorithms, and Applications II, (20 March 1998); https://doi.org/10.1117/12.303684
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