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Bernoulli Particle/Box-Particle Filters for Detection and Tracking in the Presence of Triple Measurement Uncertainty

Gning, Amadou and Ristic, B and Mihaylova, Lyudmila (2012) Bernoulli Particle/Box-Particle Filters for Detection and Tracking in the Presence of Triple Measurement Uncertainty. IEEE Transactions on Signal Processing, 60 (5). pp. 2138-2151. ISSN 1053-587X

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    Abstract

    This work presents sequential Bayesian detection and estimation methods for nonlinear dynamic stochastic systems using measurements affected by three sources of uncertainty: stochastic, set-theoretic and data association uncertainty. Following Mahler’s framework for information fusion, the paper develops the optimal Bayes filter for this problem in the form of the Bernoulli filter for interval measurements. Two numerical implementations of the optimal filter are developed. The first is the Bernoulli particle filter (PF), which turns out to require a large number of particles in order to achieve a satisfactory performance. For the sake of reduction in the number of particles, the paper also develops an implementation based on box particles, referred to as the Bernoulli Box-PF. A box particle is a random sample that occupies a small and controllable rectangular region of non-zero volume in the target state space. Manipulation of boxes utilizes the methods of interval analysis. The two implementations are compared numerically and found to perform remarkably well: the target is reliably detected and the posterior probability density function of the target state is estimated accurately. The Bernoulli Box-PF, however, when designed carefully, is computationally more efficient.

    Item Type: Article
    Journal or Publication Title: IEEE Transactions on Signal Processing
    Additional Information: (c) 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
    Uncontrolled Keywords: Sequential Bayesian Estimation ; Random Sets ; Bernoulli Filter ; Particle Filters ; Box Particle Filters ; Interval Measurements
    Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
    Departments: UNSPECIFIED
    ID Code: 52300
    Deposited By: ep_importer_pure
    Deposited On: 19 Jan 2012 16:52
    Refereed?: Yes
    Published?: Published
    Last Modified: 23 Jul 2014 14:57
    Identification Number:
    URI: http://eprints.lancs.ac.uk/id/eprint/52300

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