• Corpus ID: 88518376

Two novel costs for determining the tuning parameters of the Kalman Filter

@article{Saha2011TwoNC,
  title={Two novel costs for determining the tuning parameters of the Kalman Filter},
  author={Manika Saha and Bhaswati Goswami and Ratna Ghosh},
  journal={arXiv: Adaptation and Self-Organizing Systems},
  year={2011}
}
The Kalman filter (KF) and the extended Kalman filter (EKF) are well established techniques for state estimation. However, the choice of the filter tuning parameters still poses a major challenge for the engineers [1]. In the present work, two new costs have been proposed for determining the filter tuning parameters on the basis of the innovation covariance. This provides a cost function based method for the selection of suitable combination(s) of filter tuning parameters in order to ensure the… 

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