The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Approaches to adaptive filtering
Abstract
The different methods of adaptive filtering are divided into four categories: Bayesian, maximum likelihood (ML), correlation, and covariance matching. The relationship between the methods and the difficulties associated with each method are described. New algorithms for the direct estimation of the optimal gain of a Kalman filter are given.
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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
Cited by
Recursive Noise Adaptive Kalman Filtering by Variational Bayesian Approximations
Sarkka, S., & Nummenmaa, A. (2009) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2008.2008348 · Cited by 732
A Novel Adaptive Kalman Filter With Inaccurate Process and Measurement Noise Covariance Matrices
Huang, Y., Zhang, Y., Wu, Z., Li, N., & Chambers, J. (2018) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2017.2730480 · Cited by 731
Xiong, R., He, H., Sun, F., & Zhao, K. (2013) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2012.2222684 · Cited by 447
Applications of Kalman Filtering in Aerospace 1960 to the Present [Historical Perspectives]
Grewal, M. S., & Andrews, A. P. (2010) · IEEE Control Systems · doi:10.1109/mcs.2010.936465 · Cited by 268
Selvaraj, V., & Vairavasundaram, I. (2023) · Journal of Energy Storage · doi:10.1016/j.est.2023.108777 · Cited by 220
Metadata
- Authors
- Mehra, R.
- Venue
- IEEE Transactions on Automatic Control
- Published
- 1972-10
- Volume
- 17
- Issue
- 5
- Pages
- 693-698
- ISSN
- 0018-9286 (ISSN-L)
- OpenAlex
- W2143030612
- Cited by
- 943
- References
- 1
- FWCI
- 8.35
- Type
- journal article
- Language
- en
- Open access
- closed
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