Innovative unscented transform–based particle cardinalized probability hypothesis density filter for multi-target tracking

Bo Li, Huawei Yi, Xiaohui Li

Open source

DOI: 10.1177/0020294019877494
Published: 2019-10-21
Container: Measurement and Control
Publisher: SAGE Publications
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1177/0020294019877494,
  title = {Innovative unscented transform–based particle cardinalized probability hypothesis density filter for multi-target tracking},
  author = {Bo Li and Huawei Yi and Xiaohui Li},
  year = {2019},
  journal = {Measurement and Control},
  doi = {10.1177/0020294019877494},
  url = {https://doi.org/10.1177/0020294019877494}
}

RIS

TY  - JOUR
TI  - Innovative unscented transform–based particle cardinalized probability hypothesis density filter for multi-target tracking
AU  - Bo Li
AU  - Huawei Yi
AU  - Xiaohui Li
PY  - 2019
JO  - Measurement and Control
DO  - 10.1177/0020294019877494
UR  - https://doi.org/10.1177/0020294019877494
ER  -

APA

Li, B., Yi, H., & Li, X. (2019). Innovative unscented transform–based particle cardinalized probability hypothesis density filter for multi-target tracking. Measurement and Control. https://doi.org/10.1177/0020294019877494

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crossref · retrieved 2026-11-07T05:27:24.575Z