Gaussian Mixture Measurements for Very Long Range Tracking

Qian Zhang, Taek Lyul Song

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.

References

  1. Bar-Shalom, Y., Li, X.-R., and Kirubarajan, T. (2001). Estimation with Application to Tracking and Navigation. John Wiley and Sons.
  2. Blackman, S. and Popoli, R. (1999). Design and Analysis of Modern Tracking Systems. Artech House.
  3. Julier, S. J. and Uhlmann, J. K. (2004). Unscented filtering and nonlinear estimation. Proceedings of the IEEE, 92(3):401-422.
  4. Longbin, M., Ziaoquan, S., Yiyu, Z., and Bar-Shalom, Y. (1998). Unbiased converted measurements for tracking. IEEE Transactions on Aerospace and Electronic Systems, 34(3):1023-1027.
  5. Mus?icki, D. (2009). Bearings only single-sensor target tracking using gaussian mixtures. Automatica, 45(9):2088-2092.
  6. Mus?icki, D. and Evans, R. (2006). Measurement gaussian sum mixture target tracking. In 9th International Conference on Information Fusion, Florence, Italy.
  7. Ristic, B., Arulampalam, S., and Gordon, N. (2004). Beyond the Kalman Filter. Artech House.
  8. Singer, R. A., Sea, R., and Housewright, K. B. (1974). Derivation and evaluation of improved tracking filters for use in dense multi-target environments. IEEE Transactions on Information Theory, 20(4):423-432.
  9. Tian, X. and Bar-Shalom, Y. (2009). Coordinate conversion and tracking for very long range radars. IEEE Transactions on Aerospace and Electronic Systems, 45(3):1073-1088.
  10. Tian, X. and Bar-Shalom, Y. (2014). A consistency-based gaussian mixture filtering approach for the contact lens problem. IEEE Transactions on Aerospace and Electronic Systems, 50(3):1636-1646.
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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