Process Noise Estimation
Process Noise Estimation is a methodological framework within the broader class of state estimation techniques that specifically characterizes and quantifies the uncertainty arising from unmodeled dynamics or disturbances in the system evolution model used in Kalman filtering.
345
Publications
16.6K
Citations
859
Authors
388
Institutions
Publications per year
2017–2026
101
Parents
345
ESTIMATING DENSITY DEPENDENCE, PROCESS NOISE, AND OBSERVATION ERROR
Brian Dennis, José Miguel Ponciano, Subhash R. Lele et al. · Ecological Monographs · 2006 · 445 citations
Divergence of the Kalman filter
R.J. Fitzgerald · IEEE Transactions on Automatic Control · 1971 · 425 citations
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University at Buffalo, State University of New York, United States
4 publications · 84 citations
4
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4
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3
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388
Georgia Institute of Technology
Atlanta, United States
9 h-index
13 publications
277 citations
University of Connecticut
Storrs, United States
8 h-index
12 publications
1.1K citations
University at Buffalo, State University of New York
Buffalo, United States
6 h-index
10 publications
200 citations

Xi'an Jiaotong University
Xi'an, China
6 h-index
14 publications
437 citations

Chinese Academy of Sciences
Beijing, China
6 h-index
19 publications
895 citations

Beijing Institute of Technology
Beijing, China
6 h-index
23 publications
2K citations

Harbin Engineering University
Harbin, China
5 h-index
15 publications
670 citations

Linköping University
Linköping, Sweden
5 h-index
13 publications
333 citations
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20 publications · 2.1K citations
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10 publications · 804 citations
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9 publications · 478 citations
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8 publications · 292 citations
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6 publications · 148 citations
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