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      A Survey of Recent Advances in Particle Filters and Remaining Challenges for Multitarget Tracking

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          Abstract

          We review some advances of the particle filtering (PF) algorithm that have been achieved in the last decade in the context of target tracking, with regard to either a single target or multiple targets in the presence of false or missing data. The first part of our review is on remarkable achievements that have been made for the single-target PF from several aspects including importance proposal, computing efficiency, particle degeneracy/impoverishment and constrained/multi-modal systems. The second part of our review is on analyzing the intractable challenges raised within the general multitarget (multi-sensor) tracking due to random target birth and termination, false alarm, misdetection, measurement-to-track (M2T) uncertainty and track uncertainty. The mainstream multitarget PF approaches consist of two main classes, one based on M2T association approaches and the other not such as the finite set statistics-based PF. In either case, significant challenges remain due to unknown tracking scenarios and integrated tracking management.

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          Most cited references166

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          Multitarget bayes filtering via first-order multitarget moments

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            The Gaussian Mixture Probability Hypothesis Density Filter

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              An Overview of Existing Methods and Recent Advances in Sequential Monte Carlo

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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                23 November 2017
                December 2017
                : 17
                : 12
                : 2707
                Affiliations
                [1 ]School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an 710072, China; xuedong.wang@ 123456mail.nwpu.edu.cn (X.W.); sdsun@ 123456nwpu.edu.cn (S.S.)
                [2 ]BISITE Research Group, School of Science, University of Salamanca, 37008 Salamanca, Spain; corchado@ 123456usal.es
                Author notes
                [* ]Correspondence: t.c.li@ 123456usal.es
                Author information
                https://orcid.org/0000-0002-0499-5135
                Article
                sensors-17-02707
                10.3390/s17122707
                5750742
                29168772
                777a626c-f0e8-4544-971d-7b0327d01234
                © 2017 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 12 October 2017
                : 20 November 2017
                Categories
                Review

                Biomedical engineering
                particle filter,target tracking,nonlinear filter,monte carlo sampling,bayesian inference

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