The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Interacting multiple model methods in target tracking: a survey
Abstract
The Interacting Multiple Model (IMM) estimator is a suboptimal hybrid filter that has been shown to be one of the most cost-effective hybrid state estimation schemes. The main feature of this algorithm is its ability to estimate the state of a dynamic system with several behavior modes which can "switch" from one to another. In particular, the IMM estimator can be a self-adjusting variable-bandwidth filter, which makes it natural for tracking maneuvering targets. The importance of this approach is that it is the best compromise available currently-between complexity and performance: its computational requirements are nearly linear in the size of the problem (number of models) while its performance is almost the same as that of an algorithm with quadratic complexity. The objective of this work is to survey and put in perspective the existing IMM methods for target tracking problems. Special attention is given to the assumptions underlying each algorithm and its applicability to various situations.
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Citations
Cites
(2007) · doi:10.1007/978-3-540-71559-7 · Cited by 780
Cited by
Survey of maneuvering target tracking. part v: multiple-model methods
Li, X. R., & Jilkov, V. P. (2005) · IEEE Transactions on Aerospace and Electronic Systems · doi:10.1109/taes.2005.1561886 · Cited by 1,157
Particle filters for state estimation of jump Markov linear systems
Doucet, A., Gordon, N. J., & Kroshnamurthy, V. (2001) · IEEE Transactions on Signal Processing · doi:10.1109/78.905890 · Cited by 730
Human motion trajectory prediction: a survey
Rudenko, A., Palmieri, L., Herman, M., Kitani, K. M., Gavrila, D. M., & Arras, K. O. (2020) · The International Journal of Robotics Research · doi:10.1177/0278364920917446 · Cited by 658
Simultaneous Localization, Mapping and Moving Object Tracking
Wang, C.-C., Thorpe, C., Thrun, S., Hebert, M., & Durrant-Whyte, H. (2007) · The International Journal of Robotics Research · doi:10.1177/0278364907081229 · Cited by 596
Hovorka, R., Allen, J. M., Elleri, D., Chassin, L. J., Harris, J., Xing, D., Kollman, C., Hovorka, T., Larsen, A. M. F., Nodale, M., et al. (2010) · The Lancet · doi:10.1016/s0140-6736(09)61998-x · Cited by 450
Metadata
- Authors
- Mazor, E., Averbuch, A., Bar-Shalom, Y., & Dayan, J.
- Venue
- IEEE Transactions on Aerospace and Electronic Systems
- Published
- 1998
- Volume
- 34
- Issue
- 1
- Pages
- 103-123
- ISSN
- 0018-9251 (ISSN-L)
- OpenAlex
- W2097009900
- Cited by
- 1,179
- References
- 1
- FWCI
- 17.94
- Type
- journal article
- Language
- en
- Open access
- closed
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- Mazor, E., Averbuch, A., Bar-Shalom, Y., & Dayan, J. (1998). Interacting multiple model methods in target tracking: a survey. IEEE Transactions on Aerospace and Electronic Systems. https://doi.org/10.1109/7.640267
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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