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An improved multiple model particle filtering approach for manoeuvring target tracking using airborne GMTI with geographic information

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journal contribution
posted on 18.03.2016, 11:23 by Miao Yu, Hd Oh, Wen-Hua ChenWen-Hua Chen
This paper proposes a ground vehicle tracking method using an airborne ground moving target indicator radar where the surrounding geographic information is considered to determine vehicle's movement type as well as constrain its positions. Multiple state models corresponding to different movement modes are applied to represent the vehicle's behaviour in different terrain conditions. Based on geographic conditions and multiple state models, a constrained variable structure multiple model particle filter algorithm is proposed. Compared with the traditional multiple model particle filtering schemes, the proposed algorithm utilises a particle swarm optimisation technique which generates more effective particles and generated particles are constrained into the feasible geographic region. Numerical simulation results in a realistic environment show that the proposed method achieves better tracking performance compared with current state-of-the-art ones for manoeuvring vehicle tracking.

Funding

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

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

Aerospace Science and Technology

Volume

52

Pages

62 - 69

Citation

YU, M., OH, H. and CHEN, W-H., 2016. An improved multiple model particle filtering approach for manoeuvring target tracking using airborne GMTI with geographic information. Aerospace Science and Technology, 52, May 2016, pp. 62 - 69.

Publisher

© The Authors. Published by Elsevier Masson SAS.

Version

VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/ by/4.0/

Publication date

2016

Notes

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

ISSN

1270-9638

Language

en