Gaussian Mixture Measurements for Very Long Range Tracking

Qian Zhang, Taek Lyul Song

2015

Abstract

Target tracking with very long range is studied in this paper. Such tracking problem has severe measurement nonlinearity that will cause consistency problems and large tracking errors. Gaussian mixture measurements are obtained by dividing the measurement likelihood into several Gaussian components. The Gaussian Mixture Measurement-Integrated Track Splitting (GMM-ITS) is applied to very long range tracking scenarios. The simulation results show that the GMM-ITS can produce consistency in the filtering results crucial to the filter performance. Furthermore, it is also able to estimate the target state accurately with small tracking errors.

Paper Citation

in Harvard Style

Zhang Q. and Song T. (2015). Gaussian Mixture Measurements for Very Long Range Tracking . In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-122-9, pages 457-464. DOI: 10.5220/0005509404570464

in Bibtex Style

@conference{icinco15,
author={Qian Zhang and Taek Lyul Song},
title={Gaussian Mixture Measurements for Very Long Range Tracking},
booktitle={Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2015},
pages={457-464},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005509404570464},
isbn={978-989-758-122-9},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Gaussian Mixture Measurements for Very Long Range Tracking
SN - 978-989-758-122-9
AU - Zhang Q.
AU - Song T.
PY - 2015
SP - 457
EP - 464
DO - 10.5220/0005509404570464