The CPHD filter with target spawning
The CPHD filter with target spawning
In its classical form, the cardinalized probability hypothesis density (CPHD) filter does not model the appearance of new targets through spawning, yet there are applications for which spawning models more appropriately account for newborn objects when compared to spontaneous birth models. In this paper, we propose a principled derivation of the CPHD filter prediction step including spontaneous birth and spawning. A Gaussian Mixture implementation of the CPHD filter with spawning is then presented, illustrated with three applicable spawning models on a simulated scenario involving two parent targets spawning a total of five objects.
Bayesian estimation, Cardinalized probability hypothesis density (CPHD) filter, Multi-object filtering, point processes, random finite sets, target spawning, target tracking
13124-13138
Bryant, Daniel S.
4a2d1af8-5e1e-4a44-a68b-ee6cfccc1547
Delande, Emmanuel D.
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Gehly, Steven
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Houssineau, Jeremie
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Clark, Daniel E.
537f80e8-cbe6-41eb-b1d4-31af1f0e6393
Jones, Brandon A.
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1 March 2017
Bryant, Daniel S.
4a2d1af8-5e1e-4a44-a68b-ee6cfccc1547
Delande, Emmanuel D.
e17b3b32-0949-4914-801e-c9386bce39a5
Gehly, Steven
8885c141-656d-4054-88c8-5bd44717ffb4
Houssineau, Jeremie
89988b62-a668-4560-b49f-c1686ba7b584
Clark, Daniel E.
537f80e8-cbe6-41eb-b1d4-31af1f0e6393
Jones, Brandon A.
0655b8cc-6825-4575-82b0-0333c45a9db5
Bryant, Daniel S., Delande, Emmanuel D., Gehly, Steven, Houssineau, Jeremie, Clark, Daniel E. and Jones, Brandon A.
(2017)
The CPHD filter with target spawning.
IEEE Transactions on Signal Processing, 65 (5), .
(doi:10.1109/TSP.2016.2597126).
Abstract
In its classical form, the cardinalized probability hypothesis density (CPHD) filter does not model the appearance of new targets through spawning, yet there are applications for which spawning models more appropriately account for newborn objects when compared to spontaneous birth models. In this paper, we propose a principled derivation of the CPHD filter prediction step including spontaneous birth and spawning. A Gaussian Mixture implementation of the CPHD filter with spawning is then presented, illustrated with three applicable spawning models on a simulated scenario involving two parent targets spawning a total of five objects.
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More information
e-pub ahead of print date: 8 August 2016
Published date: 1 March 2017
Additional Information:
10.13039/501100000266-Engineering and Physical Sciences Research Council (Grant Number: EP/J015180/1)
MOD University Defence Research Centre on Signal Processing Phase 2 (Grant Number: EP/K014227/1)
Publisher Copyright:© 1991-2012 IEEE.
Keywords:
Bayesian estimation, Cardinalized probability hypothesis density (CPHD) filter, Multi-object filtering, point processes, random finite sets, target spawning, target tracking
Identifiers
Local EPrints ID: 475504
URI: http://eprints.soton.ac.uk/id/eprint/475504
ISSN: 1053-587X
PURE UUID: bfa9bbe3-4015-4da4-bc84-cc50a28a6ee9
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Date deposited: 20 Mar 2023 17:46
Last modified: 16 Mar 2024 23:15
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Contributors
Author:
Daniel S. Bryant
Author:
Emmanuel D. Delande
Author:
Steven Gehly
Author:
Jeremie Houssineau
Author:
Daniel E. Clark
Author:
Brandon A. Jones
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