Switched-Markov filtering for tracking maneuvering targets

P. D. West*, A. H. Haddad

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A new filtering concept is presented for tracking maneuvering targets. A conventional Markov switching process is used to model the target maneuver process, but a new filtering scheme is used. The filter uses a traditional track-splitting approach, with one Kalman filter tuned to each branch of the tree. To limit filter complexity, aggregation is performed over the earliest timestep of an arbitrary filter memory length. Before aggregation, a unique consistency update stage is used where each of the filter's state estimates is compared with the associated conditional model for that filter. If the two are inconsistent (e.g., a large acceleration component generated from a nonmaneuvering model), less weight is placed on that estimate. Results are presented from a full 3-D tracking model.

Original languageEnglish (US)
Title of host publicationProceedings of the American Control Conference
Editors Anon
PublisherPubl by American Automatic Control Council
Pages2299-2300
Number of pages2
ISBN (Print)0879425652
StatePublished - Dec 1 1991
EventProceedings of the 1991 American Control Conference - Boston, MA, USA
Duration: Jun 26 1991Jun 28 1991

Publication series

NameProceedings of the American Control Conference
Volume3
ISSN (Print)0743-1619

Other

OtherProceedings of the 1991 American Control Conference
CityBoston, MA, USA
Period6/26/916/28/91

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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