Abstract
The quality of kinematic positioning and navigation depends on the quality of the kinematic model describing the vehicle movements and the reliability of the measurements. A series of adaptive Kalman filters have been studied in recent years. The main principles of four kinds of adaptive filters are summarized, i.e. fading Kalman filter, adaptive Sage windowing filter, robust filter and adaptively robust filter. Some of the developed equivalent weight functions and the adaptive factors including the fading factors are also introduced. Some applications are mentioned.
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Acknowledgments
The project is sponsored by Natural Science Foundations of China (Grant Nos. 41374019 and 41020144004 as well as National 863 project No. 2013AA122501).
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Yang, Y., Xu, T., Xu, J. (2015). Principles and Comparisons of Various Adaptively Robust Filters with Applications in Geodetic Positioning. In: Kutterer, H., Seitz, F., Alkhatib, H., Schmidt, M. (eds) The 1st International Workshop on the Quality of Geodetic Observation and Monitoring Systems (QuGOMS'11). International Association of Geodesy Symposia, vol 140. Springer, Cham. https://doi.org/10.1007/978-3-319-10828-5_15
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DOI: https://doi.org/10.1007/978-3-319-10828-5_15
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