Data-driven delta-generalized labeled multi-bernoulli tracker
Abstract
A system and method for tracking a plurality of objects. Unlabeled measurement data identifying a plurality of targets corresponding to the plurality of objects is received. A multi-target likelihood function is generated using a persistent target density, a birth target density, and a clutter density. The multi-target likelihood function is used to associate persistent targets with the unlabeled measurement data to update persistent tracks and to initiate a new track for each target in the plurality of targets in the measurement data that is not associated with a persistent target.
- Inventors:
- Issue Date:
- Research Org.:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Org.:
- USDOE National Nuclear Security Administration (NNSA)
- OSTI Identifier:
- 1805516
- Patent Number(s):
- 10922820
- Application Number:
- 16/050,992
- Assignee:
- National Technology & Engineering Solutions of Sandia, LLC (Albuquerque, NM)
- DOE Contract Number:
- NA0003525
- Resource Type:
- Patent
- Resource Relation:
- Patent File Date: 07/31/2018
- Country of Publication:
- United States
- Language:
- English
Citation Formats
LeGrand, Keith Allen. Data-driven delta-generalized labeled multi-bernoulli tracker. United States: N. p., 2021.
Web.
LeGrand, Keith Allen. Data-driven delta-generalized labeled multi-bernoulli tracker. United States.
LeGrand, Keith Allen. Tue .
"Data-driven delta-generalized labeled multi-bernoulli tracker". United States. https://www.osti.gov/servlets/purl/1805516.
@article{osti_1805516,
title = {Data-driven delta-generalized labeled multi-bernoulli tracker},
author = {LeGrand, Keith Allen},
abstractNote = {A system and method for tracking a plurality of objects. Unlabeled measurement data identifying a plurality of targets corresponding to the plurality of objects is received. A multi-target likelihood function is generated using a persistent target density, a birth target density, and a clutter density. The multi-target likelihood function is used to associate persistent targets with the unlabeled measurement data to update persistent tracks and to initiate a new track for each target in the plurality of targets in the measurement data that is not associated with a persistent target.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2021},
month = {2}
}
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