Extended Kalman filter for extended object tracking

Shishan Yang; Marcus Baum

ICASSP 2017accepted0 citations

Extended Kalman filter for extended object tracking

Abstract

In this work, we present a novel method for tracking an elliptical shape approximation of an extended object based on a varying number of spatially distributed measurements. For this purpose, an explicit nonlinear measurement equation is formulated that relates the kinematic and shape parameters to a measurement by means of a multiplicative noise term. Based on the measurement equation, we derive an extended Kalman filter (EKF) for a closed-form recursive measurement update. The performance of the proposed method is demonstrated with simulations.

BibTeX

@inproceedings{icassp2017_extendedkalmanfi,
  title = {Extended Kalman filter for extended object tracking},
  author = {Shishan Yang and Marcus Baum},
  booktitle = {ICASSP 2017},
  year = {2017}
}