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Multiple Model Distributed EKF for Teams of Target Tracking UAVs using T Test Selection

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Abstract

Target tracking and estimation using teams of unmanned aerial vehicles is essential to achieving autonomous drone systems. However, one problem that degrades target estimation is the limitation of the chosen motion model to fully represent the target’s motion, especially in the case of an evasive target. This paper presents the use of multiple models as a strategy for a team of unmanned aerial vehicles to track a target of unknown behaviour. It combines the T Test criteria in a novel manner for model selection with a distributed extended Kalman filter. The algorithm is validated in both simulation and live indoor trials with a team unmanned aerial vehicles and an evasive target. Results show that using multiple models with the T Test outperforms the traditional single model methods as well as other commonly used approaches, such as the interacting multiple model and maximum likelihood methods. Furthermore, the distributed nature of the drone system provides for robust estimation, as demonstrated in live tests with occlusions present.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Royal Military College of Canada, Kingston, ON, Canada

    Sean Wolfe

  2. School of Computing, Queen’s University, Kingston, ON, Canada

    Sidney Givigi

  3. DRDC Valcartier Research Centre, Quebec, QC, Canada

    Camille-Alain Rabbath

Authors
  1. Sean Wolfe
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  2. Sidney Givigi
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  3. Camille-Alain Rabbath
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Corresponding author

Correspondence to Sidney Givigi.

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The research leading to these results was partially funded by the Natural Sciences and Engineering Research Council of Canada (NSERC) under the Discovery Grant program. Data of live trials as well as the code developed is available upon request. All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Sean Wolfe. The first draft of the manuscript was written by Sean Wolfe and posterior versions were prepared based on comments received by the other authors. All authors read and approved the final manuscript.

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Wolfe, S., Givigi, S. & Rabbath, CA. Multiple Model Distributed EKF for Teams of Target Tracking UAVs using T Test Selection. J Intell Robot Syst 104, 56 (2022). https://doi.org/10.1007/s10846-021-01513-z

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