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Chinese Intelligent Systems Conference

CISC 2016: Proceedings of 2016 Chinese Intelligent Systems Conference pp 37–49Cite as

Fading Unscented–Extended Kalman Filter for Multiple Targets Tracking with Symmetric Equations of Nonlinear Measurements

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 405))

Abstract

This paper is devoted to the problem of multiple targets tracking based on symmetric equations of nonlinear measurements. We develop a nonlinear stochastic model with unknown random bias to provide a unified structure for the tracking systems with different types of symmetric measurement equations. Moreover, the fading unscented–extended Kalman filter (FUEF) is designed to deal with the strong nonlinearities by embedding the unscented transform into the extended Kalman filter and to conduct the effect of unknown bias by inserting the fading factor. The performance of the novel filter paired with two of symmetric measurement equations are illustrated and compared by the Monte Carlo simulation results.

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Acknowledgments

This work was supported by the National Basic Research Program of China (973 Program: 2012CB821200, 2012CB821201), the NSFC (61134005, 61327807, 61521091, 61520106010, 61304232) and the Fundamental Research Funds for the Central Universities (YWF-16-GJSYS-31, YWF-16-GJSYS-32).

Author information

Authors and Affiliations

  1. The Seventh Research Division and the Center for Information and Control, School of Automation Science and Electrical Engineering, Beihang University (BUAA), 100191, Beijing, China

    Cui Zhang & Yingmin Jia

  2. The Science and Technology on Space Intelligent Control Laboratory, Beijing Institute of Control Engineering, 100190, Beijing, China

    Changqing Chen

Authors
  1. Cui Zhang
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  2. Yingmin Jia
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  3. Changqing Chen
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Corresponding author

Correspondence to Cui Zhang .

Editor information

Editors and Affiliations

  1. Beihang University , Beijing, China

    Yingmin Jia

  2. Beijing University of Posts and Telecommunications, Beijing, China

    Junping Du

  3. University of Science and Technology Beijing, Beijing, China

    Weicun Zhang

  4. Tsinghua University , Beijing, China

    Hongbo Li

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© 2016 Springer Science+Business Media Singapore

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Zhang, C., Jia, Y., Chen, C. (2016). Fading Unscented–Extended Kalman Filter for Multiple Targets Tracking with Symmetric Equations of Nonlinear Measurements. In: Jia, Y., Du, J., Zhang, W., Li, H. (eds) Proceedings of 2016 Chinese Intelligent Systems Conference. CISC 2016. Lecture Notes in Electrical Engineering, vol 405. Springer, Singapore. https://doi.org/10.1007/978-981-10-2335-4_5

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  • DOI: https://doi.org/10.1007/978-981-10-2335-4_5

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2334-7

  • Online ISBN: 978-981-10-2335-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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