A Gaussian Process based Method for Multiple Model Tracking

Mengwei Sun, Michael Davies, Ian Proudler, James Hopgood

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

Manoeuvring target tracking faces the challenge caused by the target motion model uncertainty, i.e., unknown model types or uncertain model parameters. Multiple-model (MM) methods have been generally considered to deal with this challenge, in which a bank of elemental filters is run simultaneously to provides a joint decision and estimation of motion model and localisation. However, if the uncertainty of the target trajectory increases, such as the target moves undermixed manoeuvring behaviours with time-varying parameters, more filters with different model assumptions have to be taken into account to match the motion of the target, which may lead to prohibitive computational complexity. To address this problem, we establish a training based algorithm which can learn the actual motion model as a Gaussian process (GP) regression. Then, by integrating the trained GP into the particle filter (PF), a GP-PF based tracking method is developed to track the manoeuvring targets in real-time. Monte Carlo experiments show that the proposed method had much lower tracking root mean square error (RMSE) and robustness compared with the most commonly used MM methods.
Original languageEnglish
Title of host publication2020 Sensor Signal Processing for Defence Conference (SSPD)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages5
ISBN (Electronic)978-1-7281-3810-7, 978-1-7281-3811-4
Publication statusPublished - 30 Nov 2020
Event9th International Conference of the Sensor Signal Processing for Defence - Virtual Conference, United Kingdom
Duration: 15 Sept 202016 Sept 2020


Conference9th International Conference of the Sensor Signal Processing for Defence
Abbreviated titleSSPD 2020
Country/TerritoryUnited Kingdom
CityVirtual Conference
Internet address

Keywords / Materials (for Non-textual outputs)

  • Gaussian process
  • manoeuvring target tracking
  • mixing manoeuvres
  • particle filtering


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