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Reducing the computational load of a Kalman filter

Reducing the computational load of a Kalman filter

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  • Author(s): M.J. Goris 1 ; D.A. Gray 2 ; I.M.Y. Mareels 3
    • View affiliations
    • Affiliations: 1: Netherlands Foundation for Research in Astronomy, Dwingeloo, The Netherlands
      2: Cooperative Research Centre for Sensor Signal and Information Processing, Department of Electrical and Electronic Engineering, University of Adelaide, Adelaide, Australia
      3: Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, Australia
  • Source: Volume 33, Issue 18, 28 August 1997, p. 1539 – 1541
    DOI:  10.1049/el:19971058 , Print ISSN 0013-5194, Online ISSN 1350-911X
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The Kalman filter is a powerful tool in linear-systems analysis. The authors present a particular application in which there are more measurements than states. In such an application, the state-space system can be replaced by an equivalent one that has the same number of measurements as states. The Kalman filter will produce the same state estimates for both systems. Using the equivalent system leads to a substantial saving in computer operations.

Inspec keywords: Kalman filters; linear systems; state-space methods; state estimation

Other keywords: linear-systems analysis; Kalman filter; computational load; state estimates; state-space system

Subjects: Information theory; Control system analysis and synthesis methods; General circuit analysis and synthesis methods; Signal processing and detection

References

    1. 1)
      • R.G. Brown , P.Y.C. Hwang . (1992) Introduction to random signals and applied Kalman filtering.
    2. 2)
      • Gray, D.A., Goris, M.J.: `A kalman filter based data fusion approachfor estimating the shape of a towed sonar array', Proc. Int.Conf. Neural Netw. Signal Process., 1995.
    3. 3)
      • Goris, M.: `Towed-array calibration', December 1995, PhD, Australian National University.
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