Evidential reasoning tracker: further steps toward a unified theory of sensor fusion
Α.Κ. Mahalanabis, Robert N. Lobbia, Quan Bach Nguyen · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2001
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.