Tracking of Elliptical Extended Object with Unknown but Fixed Lengths of Axes
Mingkai Li, Jian Lan, X. Rong Li · 2020
This paper studies tracking of an elliptical extended object with unknown but fixed lengths of major and minor axes. In most practical applications (e.g., tracking vehicles or aircraft carriers), the size of the extended object is time invariant, while the orientation and kinematics may change over time. In order to describe this problem accurately and improve tracking performance, we handle the problem by modeling the kinematics and orientation information as a state vector, and estimate it in a Bayesian framework. We model the unknown but fixed lengths of axes of the object as non-random parameters, and estimate them using maximum likelihood estimation (MLE). To evaluate the proposed approach, simulation results of an extended target tracking scenario are presented, which illustrate that the proposed modeling and estimation is effective.