Modeling and combining information within belief functions theory in Search And Rescue applications

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Authors
  1. Doré, P.-E.
  2. Abi-Zeid, I.
  3. Jousselme, A.-L.
  4. Martin, A.
  5. Maupin, P.
Corporate Authors
Defence R&D Canada - Valcartier, Valcartier QUE (CAN);Laval Univ, Quebec QUE (CAN)
Abstract
In this report, we study the expressiveness of the theory of belief functions in the particular case of Search And Rescue (SAR) operations. The theory of belief functions is a mathematical framework, which is used, as the probabilities, to represent the imperfections of a source of information. These imperfections are of different natures: reliability, vagueness, uncertainty, to name only a few. Representing and dealing with these imperfections in a SAR context is a major issue especially when one needs to combine and update information coming from heterogeneous and subjective sources. After having reminded some background results of the theory of optimal search, we have suggested some approaches of the SAR problem founded on the theory of belief functions.

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Keywords
belief functions;fusion;SAR;search;rescue;Koopman
Report Number
DRDC-VALCARTIER-TR-2010-224 — Technical Report
Date of publication
01 Apr 2014
Number of Pages
68
DSTKIM No
CA046836
CANDIS No
807220
Format(s):
Electronic Document(PDF)

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