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
fDate :
4/1/1993 12:00:00 AM
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;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
