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Target tracking in the framework of possibility theory : the possibilistic Bernoulli filter
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Ristic, Branko, Houssineau, Jeremie and Arulampalam, Sanjeev (2020) Target tracking in the framework of possibility theory : the possibilistic Bernoulli filter. Information Fusion, 62 . pp. 81-88. doi:10.1016/j.inffus.2020.04.008 ISSN 1566-2535.
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Official URL: https://doi.org/10.1016/j.inffus.2020.04.008
Abstract
The Bernoulli filter is a Bayes filter for joint detection and tracking of a target in the presence of false and miss detections. This paper presents a mathematical formulation of the Bernoulli filter in the framework of possibility theory, where uncertainty is represented using possibility functions, rather than probability distributions. Possibility functions model the uncertainty in a non-additive manner, and have the capacity to deal with partial (incomplete) problem specification. Thus, the main advantage of the possibilistic Bernoulli filter, derived in this paper, is that it can operate even in the absence of precise measurement and/or dynamic model parameters. This feature of the proposed filter is demonstrated in the context of target tracking using multi-static Doppler shifts as measurements.
Item Type: | Journal Article | ||||||||
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Subjects: | Q Science > QA Mathematics | ||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||||||
Library of Congress Subject Headings (LCSH): | Probabilities , Bernoulli shifts , Doppler tracking | ||||||||
Journal or Publication Title: | Information Fusion | ||||||||
Publisher: | Elsevier | ||||||||
ISSN: | 1566-2535 | ||||||||
Official Date: | October 2020 | ||||||||
Dates: |
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Volume: | 62 | ||||||||
Page Range: | pp. 81-88 | ||||||||
DOI: | 10.1016/j.inffus.2020.04.008 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||
Date of first compliant deposit: | 25 September 2020 | ||||||||
Date of first compliant Open Access: | 5 November 2021 |
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