Implementation of AKKF-based multi-sensor fusion methods in Stone Soup

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Wright, James S. and Sun, Mengwei and Davies, Mike E. and Proudler, Ian K. and Hopgood, James R.; (2024) Implementation of AKKF-based multi-sensor fusion methods in Stone Soup. In: 2024 27th International Conference on Information Fusion (FUSION). IEEE, ITA, pp. 1-7. ISBN 9781737749769 (https://doi.org/10.23919/fusion59988.2024.10706335)

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Abstract

This paper explores the increasing demand for accurate and resilient multi-sensor fusion techniques, particularly within 3D tracking systems enhanced by drone technology. Employing the adaptive kernel Kalman filter (AKKF) methodology within the Stone Soup framework, our research seeks to develop robust fusion approaches capable of seamlessly amalgamating data from a multi-sensor arrangement with fixed ground sensors and dynamic sensors mounted on drones. By capitalising on the adaptive nature of the AKKF, we aim to refine the precision and dependability of 3D object tracking in intricate scenarios. Through empirical evaluations, we illustrate the effectiveness of our proposed AKKF-based fusion strategies in enhancing tracking performance within the Stone Soup framework, thus contributing to the advancement of multi-sensor fusion methodologies within this framework.

  • Item type:Book Section
    ID code:90974
    Dates:
    Date
    Event
    11 October 2024
    Published
    Notes:The contents include material subject to ©Crown copyright (2024), Dstl. This material is licensed under the terms of the Open Government Licence except where otherwise stated. To view this licence, visit http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3 or write to the Information Policy Team, The National Archives, Kew, London TW9 4DU, or email: psi@nationalarchives.gov.uk For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission.
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:29 Oct 2024 10:58
    Last modified:21 Dec 2024 08:07
    URI:https://strathprints.strath.ac.uk/id/eprint/90974
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