In this paper, we propose a novel method for estimating an elliptic shape approximation of a moving extended object that gives rise to multiple scattered measurements per frame. For this purpose, we parameterize the elliptic shape with its orientation and the lengths of the semi-axes. We relate an individual measurement with the ellipse parameters by means of a multiplicative noise model and derive a second-order extended Kalman filter for a closed-form recursive measurement update. The benefits of the new method are discussed by means of Monte Carlo simulations for both static and dynamic scenarios.
@article{arxiv.1604.00219,
title = {Second-Order Extended Kalman Filter for Extended Object and Group Tracking},
author = {Shishan Yang and Marcus Baum},
journal= {arXiv preprint arXiv:1604.00219},
year = {2018}
}