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arXiv · 2406.10389

A Rao-Blackwellized Particle Filter for Superelliptical Extended Target Tracking

Oğul Can Yurdakul·Mehmet Çetinkaya·Enescan Çelebi·Emre Özkan
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Abstract

In this work, we propose a new method to track extended targets of different shapes such as ellipses, rectangles and rhombi. We provide an analytical framework to express these shapes as superelliptical contours and propose a Bayesian filtering scheme that can handle measurements from the contour of the object. The method utilizes the Rao-Blackwellized particle filtering algorithm with novel sensor-object geometry constraints. The success of the algorithm is demonstrated using both simulations and real-data experiments, and the algorithm has been demonstrated to be of high performance in various challenging scenarios.

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Oğul Can Yurdakul, Mehmet Çetinkaya, Enescan Çelebi, Emre Özkan. 2024-06-14. A Rao-Blackwellized Particle Filter for Superelliptical Extended Target Tracking. https://doi.org/10.23919/fusion59988.2024.10706504

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