The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
On Unscented Kalman Filtering for State Estimation of Continuous-Time Nonlinear Systems
Abstract
This paper considers the application of the unscented Kalman filter (UKF) to continuous-time filtering problems, where both the state and measurement processes are modeled as stochastic differential equations. The mean and covariance differential equations which result in the continuous-time limit of the UKF are derived. The continuous-discrete UKF is derived as a special case of the continuous-time filter, when the continuous-time prediction equations are combined with the update step of the discrete-time UKF. The filter equations are also transformed into sigma-point differential equations, which can be interpreted as matrix square root versions of the filter equations.
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Citations
Cites
A New Approach to Linear Filtering and Prediction Problems
Kalman, R. E. (1960) · Journal of Basic Engineering · doi:10.1115/1.3662552 · Cited by 31,751
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Bar‐Shalom, Y., Li, X. ‐., & Kirubarajan, T. (2002) · doi:10.1002/0471221279 · Cited by 6,782
Unscented Filtering and Nonlinear Estimation
Julier, S. J., & Uhlmann, J. K. (2004) · Proceedings of the IEEE · doi:10.1109/jproc.2003.823141 · Cited by 6,588
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New Results in Linear Filtering and Prediction Theory
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Cited by
Cubature Kalman Filtering for Continuous-Discrete Systems: Theory and Simulations
Arasaratnam, I., Haykin, S., & Hurd, T. R. (2010) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2010.2056923 · Cited by 580
Unscented Kalman filter for power system dynamic state estimation
Valverde, G., & Terzija, V. (2011) · IET Generation, Transmission & Distribution · doi:10.1049/iet-gtd.2010.0210 · Cited by 383
Applied Stochastic Differential Equations
Särkkä, S., & Solin, A. (2019) · doi:10.1017/9781108186735 · Cited by 326
Partovibakhsh, M., & Liu, G. (2015) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2014.2317781 · Cited by 301
A Systematization of the Unscented Kalman Filter Theory
Menegaz, H. M. T., Ishihara, J. Y., Borges, G. A., & Vargas, A. N. (2015) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2015.2404511 · Cited by 278
Metadata
- Authors
- Sarkka, S.
- Venue
- IEEE Transactions on Automatic Control
- Published
- 2007-09
- Volume
- 52
- Issue
- 9
- Pages
- 1631-1641
- ISSN
- 0018-9286 (ISSN-L)
- OpenAlex
- W2124202837
- Cited by
- 553
- References
- 41
- FWCI
- 16.94
- Type
- journal article
- Language
- en
- Open access
- closed
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