Bernoulli forward-backward smoothing for joint target detection and tracking
Bernoulli forward-backward smoothing for joint target detection and tracking
In this correspondence, we derive a forward-backward smoother for joint target detection and estimation and propose a sequential Monte Carlo implementation. We model the target by a Bernoulli random finite set since the target can be in one of two “present” or “absent” modes. Finite set statistics is used to derive the smoothing recursion. Our results indicate that smoothing has two distinct advantages over just using filtering: First, we are able to more accurately identify the appearance and disappearance of a target in the scene, and second, we can provide improved state estimates when the target exists
4473-4477
Vo, B.-T.
b8a660f7-8c9f-493e-97e0-07825aa1035e
Clark, D.
537f80e8-cbe6-41eb-b1d4-31af1f0e6393
Vo, B.-N.
d19a6f68-7c1f-4af0-8069-0d457c3b66ed
Ristic, B.
f51eed3b-da8d-49a8-884b-725d075c1a5e
2 June 2011
Vo, B.-T.
b8a660f7-8c9f-493e-97e0-07825aa1035e
Clark, D.
537f80e8-cbe6-41eb-b1d4-31af1f0e6393
Vo, B.-N.
d19a6f68-7c1f-4af0-8069-0d457c3b66ed
Ristic, B.
f51eed3b-da8d-49a8-884b-725d075c1a5e
Vo, B.-T., Clark, D., Vo, B.-N. and Ristic, B.
(2011)
Bernoulli forward-backward smoothing for joint target detection and tracking.
IEEE Transactions on Signal Processing, 59 (9), .
(doi:10.1109/TSP.2011.2158427).
Abstract
In this correspondence, we derive a forward-backward smoother for joint target detection and estimation and propose a sequential Monte Carlo implementation. We model the target by a Bernoulli random finite set since the target can be in one of two “present” or “absent” modes. Finite set statistics is used to derive the smoothing recursion. Our results indicate that smoothing has two distinct advantages over just using filtering: First, we are able to more accurately identify the appearance and disappearance of a target in the scene, and second, we can provide improved state estimates when the target exists
This record has no associated files available for download.
More information
Published date: 2 June 2011
Identifiers
Local EPrints ID: 473606
URI: http://eprints.soton.ac.uk/id/eprint/473606
ISSN: 1053-587X
PURE UUID: dc37f242-d311-4bd2-a450-033dc4990f3e
Catalogue record
Date deposited: 24 Jan 2023 17:52
Last modified: 16 Mar 2024 23:15
Export record
Altmetrics
Contributors
Author:
B.-T. Vo
Author:
D. Clark
Author:
B.-N. Vo
Author:
B. Ristic
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics