Tracking of Elliptical Object with Unknown but Fixed Lengths of Axes
Mingkai Li, Jian Lan, X. Rong Li
Abstract
This paper addresses the problem of tracking an elliptical object (e.g., a vehicle or aircraft carrier) with unknown but fixed lengths of axes. In practice, such axis lengths are usually time invariant, but the orientation and kinematics may be time varying. To model this extended object tracking (EOT) problem well, we represent the kinematics and orientation by a random vector, and represent the axis lengths by non-random unknown parameters. We investigate the expectation-maximization (EM) algorithm and propose an EM-based EOT approach, which utilizes the prior information about the invariant lengths and estimates the state and parameters in a unified framework. To reduce computation for real-time applications, we develop a recursive, easy to implement approach. Handy and efficient estimation of axis lengths is developed. Simulation and real-data results are presented to illustrate the effectiveness of our modeling and approach.