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Titolo:
A faster data assignment algorithm for maximum likelihood-based multitarget motion tracking with bearings-only measurements
Autore:
Chen, L; Tokuda, N;
Indirizzi:
Utsunomiya Univ, Dept Comp Sci, Utsunomiya, Tochigi 3218505, Japan Utsunomiya Univ Utsunomiya Tochigi Japan 3218505 , Tochigi 3218505, Japan
Titolo Testata:
MATHEMATICS AND COMPUTERS IN SIMULATION
fascicolo: 1-2, volume: 57, anno: 2001,
pagine: 109 - 120
SICI:
0378-4754(20010815)57:1-2<109:AFDAAF>2.0.ZU;2-G
Fonte:
ISI
Lingua:
ENG
Soggetto:
DATA ASSOCIATION;
Keywords:
bearings-only measurement; multitarget motion tracking; data association problem; Hungarian algorithm;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
20
Recensione:
Indirizzi per estratti:
Indirizzo: Tokuda, N Utsunomiya Univ, Dept Comp Sci, Utsunomiya, Tochigi 3218505, Japan Utsunomiya Univ Utsunomiya Tochigi Japan 3218505 3218505, Japan
Citazione:
L. Chen e N. Tokuda, "A faster data assignment algorithm for maximum likelihood-based multitarget motion tracking with bearings-only measurements", MATH COMP S, 57(1-2), 2001, pp. 109-120

Abstract

We have proved a new rotational sorting algorithm capable of reducing the complexity of data assignment process embedded in the maximum likelihood (ML)-based solution of a multitarget tracking problem from O(N-3) of the conventional Hungarian type routines to O(N-2) provided that the bearings-only measurements from an array of passive sensors are free from cluttering and missing data. (C) 2001 IMACS. Published by Elsevier Science B.V. All rightsreserved.

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Documento generato il 04/04/20 alle ore 14:39:58