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Published in:
Absolute and Relative Gravimetry Read chapter Read first chapter

2010 | OriginalPaper | Chapter

2. Adaptively Robust Kalman Filters with Applications in Navigation

Author : Yuanxi Yang

Published in: Sciences of Geodesy - I

Publisher: Springer Berlin Heidelberg

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Abstract

A new adaptively robust Kalman filtering was developed in 2001. The main achievements of the adaptively robust filter are summarized from the published papers in recent years. These include the establishment of the principle of the adaptively robust filter, the derivation of the corresponding state parameter estimator, the developments of four adaptive factors for balancing the contribution of kinematic model information and measurements, which include three-segment function, two-segment function, exponential function and zero and one function for state component adaptation, and the establishment of four kinds of learning statistics for judging the kinematic model errors, which include state discrepancy statistic, predicted residual statistic, variance component ratio statistic and velocity discrepancy statistic. The relations of the adaptively robust filter with standard Kalman filter, robust filter and some other adaptive Kalman filters as well as some related adjustment methods are depicted by a figure. Other developments of the adaptively robust filter are also presented.

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Metadata
Title
Adaptively Robust Kalman Filters with Applications in Navigation
Author
Yuanxi Yang
Copyright Year
2010
Publisher
Springer Berlin Heidelberg
Book
Sciences of Geodesy - I

Print ISBN: 978-3-642-11740-4

Electronic ISBN: 978-3-642-11741-1

Copyright Year: 2010

DOI
https://doi.org/10.1007/978-3-642-11741-1_2

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