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Cited by 207

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Multitarget Tracking

Vo, Ba‐ngu, Mallick, Mahendra, Bar‐shalom, Yaakov, Coraluppi, Stefano, Osborne, Richard, Mahler, Ronald, Vo, Ba‐tuong·2015·Wiley Encyclopedia of Electrical and Electronics Engineering

Abstract

Multitarget tracking (MTT) refers to the problem of jointly estimating the number of targets and their states or trajectories from noisy sensor measurements. MTT has a long history spanning over 50 years, with a plethora of applications in many fields of study. While numerous techniques have been developed, the three most widely used approaches to MTT are the joint probabilistic data association filter (JPDAF), multiple hypothesis tracking (MHT), and random finite set (RFS). The JPDAF and MHT have been widely used for more than two decades, while the RFS‐based MTT algorithms have received a great deal of attention during the last decade. In this article, we provide an overview of MTT and succinct summaries of popular state‐of‐the‐art MTT algorithms.

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Metadata

Authors
Vo, B., Mallick, M., Bar‐shalom, Y., Coraluppi, S., Osborne, R., Mahler, R., & Vo, B.
Venue
Wiley Encyclopedia of Electrical and Electronics Engineering
Publisher
Wiley
Published
2015-09-15
Pages
1-15
OpenAlex
W4211164258
Cited by
207
References
4
Type
reference entry
Language
en
Open access
closed

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CoChat. (2026). Citation check: Multitarget Tracking. https://app.cochat.ai/papers/10.1002/047134608x.w8275
The paper
Vo, B., Mallick, M., Bar‐shalom, Y., Coraluppi, S., Osborne, R., Mahler, R., & Vo, B. (2015). Multitarget Tracking. Wiley Encyclopedia of Electrical and Electronics Engineering. https://doi.org/10.1002/047134608x.w8275

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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.