An improved resampling approach for particle filters in tracking

dc.contributor.authorYu Gong
dc.contributor.authorSangarapillai Lambotharan
dc.contributor.authorAbdullahi Daniyan
dc.date.accessioned2025-04-25T10:10:58Z
dc.date.issued2017-11-06
dc.date.issued2017-08-01
dc.date.issued2019-03-27
dc.description.abstractResampling is an essential step in particle filtering (PF) methods in order to avoid degeneracy. Systematic resampling is one of a number of resampling techniques commonly used due to some of its desirable properties such as ease of implementation and low computational complexity. However, it has a tendency of resampling very low weight particles especially when a large number of resampled particles are required which may affect state estimation. In this paper, we propose an improved version of the systematic resampling technique which addresses this problem and demonstrate performance improvement.
dc.identifier10.1109/icdsp.2017.8096095
dc.identifier2767646790
dc.identifier.otherDOI: 10.1109/ICDSP.2017.8096095
dc.identifier.urihttp://repository.futminna.edu.ng:4000/handle/123456789/986
dc.publisherIEEE
dc.sourceUnpayWall
dc.sourceCrossref
dc.sourceMicrosoft Academic Graph
dc.subjectSystematics
dc.subjectTarget tracking
dc.subjectApproximation algorithms
dc.subjectMonte Carlo methods
dc.subjectRandom number generation
dc.subjectComputational complexity
dc.subjectState-space methods
dc.titleAn improved resampling approach for particle filters in tracking
dc.typeOther

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