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Title: Data association using game theory for multi-target tracking in passive bistatic radar
Authors: Daniyan, Abdullahi
Aldowesh, Abdulrazaq
Gong, Yu
Lambotharan, Sangarapillai
Keywords: Game theory
Data association
Multi-target tracking
Passive bi-static radar PBR
Particle filter
Sequential Monte Carlo (SMC)
PHD filter
Issue Date: 2017
Publisher: © IEEE
Citation: DANIYAN, A. ... et al, 2017. Data association using game theory for multi-target tracking in passive bistatic radar. Presented at the 2017 IEEE Radar Conference (RadarConf), Seattle, WA, USA, 8-12 May 2017, pp.0042-0046.
Abstract: We investigate a game theoretic data association technique for multi-target tracking (MTT) with varying number of targets in a real passive bi-static radar (PBR) environment. The radar measurements were obtained through a PBR developed using National Instrument (NI) Universal Software Radio Peripheral (USRP). We considered the problem of associating target state-estimates-to-tracks for varying number of targets. We use the sequential Monte Carlo probability hypothesis density (SMC-PHD) filter to perform the multi-target tracking in order to obtain the target state estimates and model the interaction between target tracks as a game. Experimental results using this real radar data demonstrate effectiveness of the game theoretic data association for multiple target tracking.
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/RADAR.2017.7944168
URI: https://dspace.lboro.ac.uk/2134/37350
Publisher Link: https://doi.org/10.1109/RADAR.2017.7944168
ISBN: 9781467388238
Appears in Collections:Conference Papers and Presentations (Mechanical, Electrical and Manufacturing Engineering)
Conference Papers and Presentations (Aeronautical and Automotive Engineering)

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