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Robustizing Kalman filters with the M-estimating functions

  • Pak, Ro Jin (Department of Applied Statistics, Dankook University)
  • Received : 2017.10.27
  • Accepted : 2017.12.02
  • Published : 2018.01.31

Abstract

This article considers a robust Kalman filter from the M-estimation point of view. Pak (Journal of the Korean Statistical Society, 27, 507-514, 1998) proposed a particular M-estimating function which has the data-based shaping constants. The Kalman filter with the proposed M-estimating function is considered. The structure and the estimating algorithm of the Kalman filter accompanying the M-estimating function are mentioned. Kalman filter estimates by the proposed M-estimating function are shown to be well behaved even when data are contaminated.

Keywords

References

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