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26 November 2001 Evidential reasoning tracker: further steps toward a unified theory of sensor fusion
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The discipline of Sensor and Data Fusion in increasingly characterized by a set of disparate tools and principles. An initial consideration of these principles belies any theoretical coherence or commonality. Yet secondary inspection may begin to reveal a fundamental basis that ties together these algorithms. This paper represents the second in a multi-part discussion that attempts to explore this common basis. In particular, while our first discussion centered around the use of a traditional state estimation technique (Kalman Filtering) to perform decision-level identify fusion, in the paper we take the opposite approach, using a traditional decision-level ID technique (Dempster-Shafer Calculus) to do state estimation.
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Arijit Mahalanabis, Robert N. Lobbia, and Quan Bach Nguyen "Evidential reasoning tracker: further steps toward a unified theory of sensor fusion", Proc. SPIE 4473, Signal and Data Processing of Small Targets 2001, (26 November 2001); doi: 10.1117/12.492811;


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