DocumentCode
882557
Title
A fast method for finding the exact N -best hypotheses for multitarget tracking
Author
Danchick, R. ; Newnam, G.E.
Author_Institution
TRW Systems Integration Group, Redondo Beach, CA
Volume
29
Issue
2
fYear
1993
fDate
4/1/1993 12:00:00 AM
Firstpage
555
Lastpage
560
Abstract
The necessity for multiple hypothesis tracking (MHT) is recognized throughout the SDI tracking community. However, implementations of MHT techniques have required enormous amounts of computer time and memory. An efficient method of measurement-to-target association that makes MHT practical for the first time is presented. The method finds the exact N -best feasible hypotheses directly from a sequence of linear assignment problem solutions
Keywords
probability; sensor fusion; tracking; Kalman filters; SDI tracking; computer memory; computer time; exact N-best hypotheses; linear assignment problem solutions; measurement-to-target association; multiple hypothesis tracking; multitarget tracking; sensors; Accuracy; Clustering algorithms; Error probability; Integer linear programming; Milling machines; NASA; Notice of Violation; Partitioning algorithms; Space technology; Time measurement; Writing;
fLanguage
English
Journal_Title
Aerospace and Electronic Systems, IEEE Transactions on
Publisher
ieee
ISSN
0018-9251
Type
jour
DOI
10.1109/7.210093
Filename
210093
Link To Document