The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
Bayesian estimation and the Kalman filter
Open accessOverview
Integrity signals
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Cites
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Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“To enable real-time tracking, the estimated model of the objects dynamics is coupled with an EKF [3] for robustness against noisy sensing.”
From Catching Objects in Flight (2014) · cites this paper as [3]
Citations
Cites
A tutorial on hidden Markov models and selected applications in speech recognition
Rabiner, L. R. (1989) · Proceedings of the IEEE · doi:10.1109/5.18626 · Cited by 22,743
Applied Multivariate Statistical Analysis.
Johnson, A. R., & Wichern, D. W. (1988) · Biometrics · doi:10.2307/2531616 · Cited by 11,353
Introduction to automata theory, languages and computation
(1981) · Mathematics and Computers in Simulation · doi:10.1016/0378-4754(81)90068-9 · Cited by 10,699
Statistical Decision Theory and Bayesian Analysis
Berger, J. O. (1985) · Springer Series in Statistics · doi:10.1007/978-1-4757-4286-2 · Cited by 7,722
Introduction to automata theory, languages, and computation
(1980) · Computer Languages · doi:10.1016/0096-0551(80)90011-9 · Cited by 6,824
Applied Optimal Control: Optimization, Estimation, and Control
Bryson, A. E., & Ho, Y.-C. (2018) · Routledge eBooks · doi:10.1201/9781315137667 · Cited by 6,015
Bar‐Shalom, Y. (1988) · Medical Entomology and Zoology · Cited by 3,157
J., J. E. (1979) · Technometrics · doi:10.1080/00401706.1979.10489803 · Cited by 3,073
Bar-Shalom, Y., Fortmann, T. E., & Cable, P. G. (1990) · The Journal of the Acoustical Society of America · doi:10.1121/1.398863 · Cited by 3,070
Stastical Decision Theory and Bayesian Analysis.
Ghosh, M., & Berger, J. (1988) · Journal of the American Statistical Association · doi:10.2307/2288950 · Cited by 2,905
Cited by
Kim, S., Shukla, A., & Billard, A. (2014) · IEEE Transactions on Robotics · doi:10.1109/tro.2014.2316022 · Cited by 220
Estimating the non-linear dynamics of free-flying objects
Kim, S., & Billard, A. (2012) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2012.05.022 · Cited by 55
Learning motion dynamics to catch a moving object
Kim, S., Gribovskaya, E., & Billard, A. (2010) · 2010 10th IEEE-RAS International Conference on Humanoid Robots · doi:10.1109/ichr.2010.5686332 · Cited by 39
Metadata
- Authors
- Barker, A. L., Brown, D. E., & Martin, W. N.
- Affiliations
- University of Virginia (US)
- ORCID
- Brown, D.E.
- Venue
- Computers & Mathematics with Applications
- Publisher
- Elsevier BV
- Published
- 1995-11
- Volume
- 30
- Issue
- 10
- Pages
- 55-77
- ISSN
- 0898-1221 (ISSN-L)
- OpenAlex
- W2168670302
- Cited by
- 78
- References
- 29
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 10 · 2023: 7 · 2022: 8 · 2021: 7 · 2020: 7 · 2019: 5 · 2017: 2 · 2016: 1 · 2015: 1 · 2014: 4 · 2013: 2 · 2012: 1
- FWCI
- 0.45
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 6468 d)
- Locations
- Computers & Mathematics with Applications (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Target Tracking and Data Fusion in Sensor Networks
- Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
- Physical Sciences › Computer Science › Artificial Intelligence › Gaussian Processes and Bayesian Inference
- Keywords
- Kalman filter, Bayesian state estimation, discrete-time Markov chains, Gaussian random vectors, linear Gaussian models, probabilistic Turing machines, dynamic classification, moving object tracking
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Bayesian estimation and the Kalman filter. https://app.cochat.ai/papers/10.1016/0898-1221(95)00156-s
- The paper
- Barker, A. L., Brown, D. E., & Martin, W. N. (1995). Bayesian estimation and the Kalman filter. Computers & Mathematics with Applications. https://doi.org/10.1016/0898-1221(95)00156-s
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
