Second-Order Extended Kalman Filter for Extended Object and Group Tracking
It addresses the problem of tracking extended objects with elliptic shapes for tracking and sensor fusion applications, offering a closed-form recursive update.
The paper proposes a second-order extended Kalman filter for tracking elliptic extended objects using a multiplicative noise model, achieving improved estimation accuracy in Monte Carlo simulations.
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.