Extended object tracking based on superellipses
Lin Gao, Giorgio Battistelli, Luigi Chisci · 2024
This paper presents an approach for 2-dimensional extended object tracking (EOT). The extended object (EO) is represented as a superellipse characterized by kinematic and shape states, with the latter uniquely specified in terms of four parameters. An approximated measurement model is proposed accounting for the fact that the measurements can be generated from any position inside or on the contour of the EO. Then, EOT is performed by iteratively estimating the kinematic state via a Kalman filter, while the posterior of the shape state is represented and propagated in particle filter form due to the strong nonlinearity of the resulting shape measurement model. Simulation results are provided to assess the performance of the proposed method.