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Adaptive Nonlinear Information Filters for Multiple Sensor Fusion

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Informatics in Control, Automation and Robotics 12th International Conference, ICINCO 2015 Colmar, France, July 21-23, 2015 Revised Selected Papers

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 383))

Abstract

This paper addresses the problem of multiple sensor fusion in situations when the system dynamics is affected by unknown parameter variation and proposes a set of adaptive nonlinear information filters. For the above estimation problem complete knowledge of the process noise covariance (Q) remains unavailable due to unknown parameter variation. The proposed varieties of adaptive nonlinear information filters are so designed that they can present satisfactory estimation performance in the face of parametric uncertainty by online adaptation of unknown \({{\varvec{Q}}}\). The adaptation steps incorporated in the algorithms have been formulated using Maximum Likelihood Estimation method. Superiority of the adaptive information filters over their non adaptive counterparts is demonstrated in simulation considering a case study where a maneuvering aircraft is to be tracked using multiple radars. Additionally, comparison of performance of proposed alternative adaptive filters is also carried out to appreciate the relative advantages of the proposed variants of adaptive information filters for multiple sensor fusion.

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Notes

  1. 1.

    The present paper is an extended version of the conference paper [14] presented in 12th International Conference on Informatics in Control, Automation and Robotics, 2015.

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Acknowledgments

The first author thanks Council of Scientific and Industrial Research, New Delhi, India for financial support and expresses his gratitude to Centre for Knowledge Based System, Jadavpur University, Kolkata, India for infrastructural support.

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Authors and Affiliations

  1. Department of Electrical Engineering, Jadavpur University, Kolkata, 700032, India

    Aritro Dey, Smita Sadhu & Tapan Kumar Ghoshal

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  1. Aritro Dey
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  2. Smita Sadhu
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  3. Tapan Kumar Ghoshal
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Correspondence to Aritro Dey .

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Editors and Affiliations

  1. Polytechnic Institute of Setúbal, Setubal, Portugal

    Joaquim Filipe

  2. Vitry sur Seine, France

    Kurosh Madani

  3. Ford Research & Adv. Engineering, Dearborn, Michigan, USA

    Oleg Gusikhin

  4. Mechanical and Aerospace Engineering, Carleton University, Ottawa, Ontario, Canada

    Jurek Sasiadek

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Dey, A., Sadhu, S., Ghoshal, T.K. (2016). Adaptive Nonlinear Information Filters for Multiple Sensor Fusion. In: Filipe, J., Madani, K., Gusikhin, O., Sasiadek, J. (eds) Informatics in Control, Automation and Robotics 12th International Conference, ICINCO 2015 Colmar, France, July 21-23, 2015 Revised Selected Papers. Lecture Notes in Electrical Engineering, vol 383. Springer, Cham. https://doi.org/10.1007/978-3-319-31898-1_21

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  • DOI: https://doi.org/10.1007/978-3-319-31898-1_21

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