A generalized Kalman filter with its precision in recursive form when the stochastic model is misspecified

Teunissen, P.J.G.; Khodabandeh, A.; Psychas, D.V.

doi:10.1007/s00190-021-01562-0

A generalized Kalman filter with its precision in recursive form when the stochastic model is misspecified

Title

A generalized Kalman filter with its precision in recursive form when the stochastic model is misspecified

Author

Teunissen, P.J.G. (TU Delft Mathematical Geodesy and Positioning; University of Melbourne; Curtin University)
Khodabandeh, A. (University of Melbourne)
Psychas, D.V. (TU Delft Mathematical Geodesy and Positioning)

Date

2021

Abstract

In this contribution, we introduce a generalized Kalman filter with precision in recursive form when the stochastic model is misspecified. The filter allows for a relaxed dynamic model in which not all state vector elements are connected in time. The filter is equipped with a recursion of the actual error-variance matrices so as to provide an easy-to-use tool for the efficient and rigorous precision analysis of the filter in case the underlying stochastic model is misspecified. Different mechanizations of the filter are presented, including a generalization of the concept of predicted residuals as needed for the recursive quality control of the filter.

Subject

Error-variance matrices
Generalized filter
Kalman filter
Minimal detectable bias (MDB)
Predicted residual
Stochastic model

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http://resolver.tudelft.nl/uuid:ebdc6b9d-feac-4ce9-a68c-2498d5723b3c

DOI

https://doi.org/10.1007/s00190-021-01562-0

ISSN

0949-7714

Source

Journal of Geodesy, 95 (9)

Part of collection

Institutional Repository