The DOI matches its Crossref record; the references it cites are not checked yet.
Maximum Likelihood Identification of Stochastic Models of Inertial Sensor Noises
Published version of a preprint
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
The citation lists haven’t been fetched yet
Cited by 4
Research works printed but not linked: 26
- 10.2514/3.21398 · doi:10.2514/3.21398
- 10.1002/0471221279 · DOI · Paper page
- 10.23919/FUSION59988.2024.10706415 · doi:10.23919/fusion59988.2024.10706415
- 10.3390/s91108473 · doi:10.3390/s91108473
- 10.1109/MCS.2022.3209059 · DOI
- 10.1109/JSEN.2016.2565389 · doi:10.1109/jsen.2016.2565389
- 10.1002/navi.119 · doi:10.1002/navi.119
- 2006, IEEE Standard Specification Format Guide and Test Procedure for Single-Axis Laser Gyros
- 10.1109/TAC.1970.1099344 · doi:10.1109/tac.1970.1099344
- Kay, 1993, Fundamentals of Statistical Processing: Estimation Theory
- 10.1109/TAES.2019.2917986 · doi:10.1109/taes.2019.2917986
- 10.1109/TAES.2003.1261132 · DOI · Paper page
- Nassar, 2005, Accurate INSIDGPS positioning using INS data de-noising and autoregressive (AR) modeling of inertial sensor errors, Geomatica, 59, 283
- 10.1109/JSEN.2015.2476668 · DOI
- 10.1198/07350010152596736 · DOI
- Saini, 2010, Online estimation of state space error model for MEMS IMU, J. Model. Simul. Syst., 1, 219
- 10.1088/0957-0233/22/8/085204 · DOI
- Thomas, 2016, Bias and measurement error in comparative analyses: A case study with the Ornstein–Uhlenbeck model, Biol. J. Linnean Soc., 118, 64
- 10.1109/PLANS.2012.6236828 · doi:10.1109/plans.2012.6236828
- 10.1109/TIM.2011.2171609 · DOI
- 10.1007/978-3-319-95117-1_9 · doi:10.1007/978-3-319-95117-1_9
- 10.1109/LCSYS.2018.2840878 · doi:10.1109/lcsys.2018.2840878
- 10.23919/FUSION59988.2024.10706529 · DOI
- 10.1117/12.3016575 · doi:10.1117/12.3016575
- 10.1109/ACCESS.2020.2982407 · DOI
- Zhao, 2011, Stochastic modeling and analysis of IMU sensor errors, Arch. Photogramm., Cartography Remote Sens., 22, 437
Metadata
- Authors
- Ye, S., Bar-Shalom, Y., Willett, P., & Zaki, A. S.
- Venue
- IEEE Sensors Journal
- Published
- 2024-12-15
- Volume
- 24
- Issue
- 24
- Pages
- 41021-41028
- ISSN
- 1530-437X
- 1558-1748
- 2379-9153
- Cited by
- 4
- Licence
- Funders
- National Institute for Undersea Vehicle Technology/Office of Naval Research Project COM-49.
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 ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Maximum Likelihood Identification of Stochastic Models of Inertial Sensor Noises. https://app.cochat.ai/papers/10.1109/jsen.2024.3487542
- The paper
- Ye, S., Bar-Shalom, Y., Willett, P., & Zaki, A. S. (2024). Maximum Likelihood Identification of Stochastic Models of Inertial Sensor Noises. IEEE Sensors Journal. https://doi.org/10.1109/jsen.2024.3487542
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.
