The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Gaussian filters for nonlinear filtering problems
Abstract
We develop and analyze real-time and accurate filters for nonlinear filtering problems based on the Gaussian distributions. We present the systematic formulation of Gaussian filters and develop efficient and accurate numerical integration of the optimal filter. We also discuss the mixed Gaussian filters in which the conditional probability density is approximated by the sum of Gaussian distributions. A new update rule of weights for Gaussian sum filters is proposed. Our numerical tests demonstrate that new filters significantly improve the extended Kalman filter with no additional cost, and the new Gaussian sum filter has a nearly optimal performance.
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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
Numerical Methods for Unconstrained Optimization and Nonlinear Equations
Dennis, J. E., & Schnabel, R. B. (1996) · Society for Industrial and Applied Mathematics eBooks · doi:10.1137/1.9781611971200 · Cited by 7,615
A new approach for filtering nonlinear systems
Julier, S. J., Uhlmann, J. K., & Durrant-Whyte, H. F. (2005) · Proceedings of 1995 American Control Conference - ACC'95 · doi:10.1109/acc.1995.529783 · Cited by 1,926
Estimation and Tracking: Principles, Techniques, and Software
Bar‐Shalom, Y., & Li, X. (1993) · Medical Entomology and Zoology · Cited by 1,910
Nonlinear Bayesian estimation using Gaussian sum approximations
Alspach, D., & Sorenson, H. (1972) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1972.1100034 · Cited by 1,239
Recursive bayesian estimation using gaussian sums
Sorenson, H. W., & Alspach, D. L. (1971) · Automatica · doi:10.1016/0005-1098(71)90097-5 · Cited by 952
Some Modified Matrix Eigenvalue Problems
Golub, G. H. (1973) · SIAM Review · doi:10.1137/1015032 · Cited by 728
Numerical Methods for Unconstrained Optimization and Nonlinear Equations.
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Suboptimal state estimation for continuous-time nonlinear systems from discrete noisy measurements
Athans, M., Wishner, R., & Bertolini, A. (1968) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1968.1098986 · Cited by 395
Approximations to optimal nonlinear filters
Kushner, H. J. (1967) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1967.1098671 · Cited by 314
Cited by
Arasaratnam, I., & Haykin, S. (2009) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2009.2019800 · Cited by 3,380
Kalman Filtering and Neural Networks
(2001) · Wiley eBooks · doi:10.1002/0471221546 · Cited by 2,386
Sigma-Point Kalman Filters for Probabilistic Inference in Dynamic State-Space Models
van der Merwe, R. (2004) · doi:10.6083/m4z60kz5 · Cited by 1,017
An Overview of Existing Methods and Recent Advances in Sequential Monte Carlo
Cappe, O., Godsill, S. J., & Moulines, E. (2007) · Proceedings of the IEEE · doi:10.1109/jproc.2007.893250 · Cited by 1,009
Nonlinear filters: beyond the Kalman filter
Daum, F. (2005) · IEEE Aerospace and Electronic Systems Magazine · doi:10.1109/maes.2005.1499276 · Cited by 673
Metadata
- Authors
- Ito, K., & Xiong, K.
- Venue
- IEEE Transactions on Automatic Control
- Published
- 2000-05
- Volume
- 45
- Issue
- 5
- Pages
- 910-927
- ISSN
- 0018-9286 (ISSN-L)
- OpenAlex
- W2099371695
- Cited by
- 1,498
- References
- 10
- FWCI
- 8.75
- Type
- journal article
- Language
- en
- Open access
- closed
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