Abstract.
A robust Kalman filter is derived for rank deficient observation models. The datum for the Kalman filter is introduced at the zero epoch by the choice of a generalized inverse. The robust filter is obtained by Bayesian statistics and by applying a robust M-estimate. Outliers are not only looked for in the observations but also in the updated parameters. The ability of the robust Kalman filter to detect outliers is demonstrated by an example.
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Received: 8 November 1996 / Accepted: 11 February 1998
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Koch, K., Yang, Y. Robust Kalman filter for rank deficient observation models. Journal of Geodesy 72, 436–441 (1998). https://doi.org/10.1007/s001900050183
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DOI: https://doi.org/10.1007/s001900050183