Keywords
Kalman filters, decision theory, position control, tracking
Abstract
A decision philosophy that seeks the avoidance of error by trading off belief of truth and value of information is applied to the problem of recognizing tracks from multiple targets (MTT). A successful MTT methodology should be robust in that its performance degrades gracefully as the conditions of the collection become less favorable to optimal operation. By stressing the avoidance, rather than the explicit minimization, of error, the authors obtain a decision rule for trajectory-data association that does not require the resolution of all conflicting hypotheses when the database does not contain sufficient information to do so reliably. This rule, coupled with a set-valued Kalman filter for trajectory estimation, results in a methodology that does not attempt to extract more information from the database than it contains.
Original Publication Citation
Moon, T. K., et al. "Epistemic Decision Theory Applied to Multiple-Target Tracking." Systems, Man and Cybernetics, IEEE Transactions on 24.2 (1994): 234-45
BYU ScholarsArchive Citation
Stirling, Wynn C.; Moon, T. K.; Budge, S. E.; and Thompson, J. B., "Epistemic decision theory applied to multiple-target tracking" (1994). Faculty Publications. 703.
https://scholarsarchive.byu.edu/facpub/703
Document Type
Peer-Reviewed Article
Publication Date
1994-02-01
Permanent URL
http://hdl.lib.byu.edu/1877/1052
Publisher
IEEE
Language
English
College
Ira A. Fulton College of Engineering and Technology
Department
Electrical and Computer Engineering
Copyright Status
© 1994 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Copyright Use Information
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