Loughborough University
Browse
IEEE-07707385.pdf (1.56 MB)

New multiple target tracking strategy using domain knowledge and optimisation

Download (1.56 MB)
journal contribution
posted on 2016-09-30, 11:18 authored by Runxiao Ding, Miao Yu, Hyondong Oh, Wen-Hua ChenWen-Hua Chen
This paper proposes an environment-dependent vehicle dynamic modelling approach considering interactions between the noisy control input of a dynamic model and the environment in order to make best use of domain knowledge. Based on this modelling, a new domain knowledge-aided moving horizon estimation (DMHE) method is proposed for ground moving target tracking. The proposed method incorporates different types of domain knowledge in the estimation process considering both environmental physical constraints and interaction behaviours between targets and the environment. Furthermore, in order to deal with a data association ambiguity problem of multiple target tracking in a cluttered environment, the DMHE is combined with a multiple hypothesis tracking structure. Numerical simulation results show that the proposed DMHE-based method and its extension could achieve better performance than traditional tracking methods which utilise no domain knowledge or simple physical constraint information only.

Funding

This work was supported by the UK Engineering and Physical Sciences Research Council (EPSRC) Grant number EP/K014307/1 and the MOD University Defence Research Collaboration in Signal Processing.

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

IEEE Transactions on Systems, Man and Cybernetics: Systems

Volume

47

Issue

4

Pages

605 - 616

Citation

DING, R. ...et al., 2016. New multiple target tracking strategy using domain knowledge and optimisation. IEEE Transactions on Systems, Man and Cybernetics: Systems, 47 (4), pp.605-616

Publisher

IEEE © the authors

Version

  • VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

2016-09-19

Publication date

2016-10-26

Notes

This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/

ISSN

2168-2216

eISSN

2168-2232

Language

  • en