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Multiresolutional Filtering of a Class of Dynamic Multiscale System Subject to Colored State Equation Noise

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Distributed Computing in Sensor Systems (DCOSS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 3560))

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Abstract

In this paper, modeling and estimation of a class of dynamic multiscale system subject to colored state equation noise is proposed. The colored state noise vector is augmented in the system state variables, the state space projection equation is used to link the scales, and then a new system model is built. The new model is in a form suitable for the application of the Kalman filter equations. Haar-wavelet-based model and estimation algorithm are given. Monte Carlo simulation results demonstrate that the proposed algorithm is effective and powerful in this kind of multiscale estimation problem.

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Author information

Authors and Affiliations

  1. Department of Automation, Tsinghua University, Beijing, 100084, China

    Peiling Cui & Guizeng Wang

  2. Department of Automatic Control, Northwestern Polytechnical University, Xi’an, Shaanxi, 710072, China

    Peiling Cui, Quan Pan & Jianfeng Cui

Authors
  1. Peiling Cui
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  2. Quan Pan
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  3. Guizeng Wang
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  4. Jianfeng Cui
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Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, University of Southern California, 90089-2562, Los Angeles, CA, USA

    Viktor K. Prasanna

  2. Department of Computer Science, Louisiana State University, Baton Rouge, USA

    Sitharama S. Iyengar

  3. Department of Computer Engineering and Informatics, University of Patras, 26500, Rio, Patras, Greece

    Paul G. Spirakis

  4. School of Engineering and Applied Sciences, Harvard University, 02138, Cambridge, MA, USA

    Matt Welsh

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© 2005 Springer-Verlag Berlin Heidelberg

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Cui, P., Pan, Q., Wang, G., Cui, J. (2005). Multiresolutional Filtering of a Class of Dynamic Multiscale System Subject to Colored State Equation Noise. In: Prasanna, V.K., Iyengar, S.S., Spirakis, P.G., Welsh, M. (eds) Distributed Computing in Sensor Systems. DCOSS 2005. Lecture Notes in Computer Science, vol 3560. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11502593_18

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  • DOI: https://doi.org/10.1007/11502593_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26422-4

  • Online ISBN: 978-3-540-31671-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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