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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/37349

Title: An improved resampling approach for particle filters in tracking
Authors: Daniyan, Abdullahi
Gong, Yu
Lambotharan, Sangarapillai
Keywords: Resampling
Particle filters
Sequential Monte Carlo (SMC) methods
Systematic resampling
Issue Date: 2017
Publisher: © IEEE
Citation: DANIYAN, A., GONG, Y. and LAMBOTHARAN, S., 2017. An improved resampling approach for particle filters in tracking. Presented at the 2017 22nd International Conference on Digital Signal Processing (DSP), London, UK, 23-25 August 2017.
Abstract: Resampling 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.
Description: © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works.
Sponsor: This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) Grant number EP/K014307/1, the MOD University Defence Research Collaboration (UDRC) in Signal Processing, UK and the Petroleum Technology Development Fund (PTDF), Nigeria.
Version: Accepted for publication
DOI: 10.1109/icdsp.2017.8096095
URI: https://dspace.lboro.ac.uk/2134/37349
Publisher Link: https://doi.org/10.1109/icdsp.2017.8096095
ISBN: 9781538618950
ISSN: 2165-3577
Appears in Collections:Conference Papers and Presentations (Mechanical, Electrical and Manufacturing Engineering)
Conference Papers and Presentations (Aeronautical and Automotive Engineering)

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