DocumentCode
901039
Title
Feature-mapping data fusion
Author
Wang, F. ; Litva, J. ; Lo, T. ; Bossé, E. ; Leung, H.
Author_Institution
Commun. Res. Lab., McMaster Univ., Hamilton, Ont., Canada
Volume
143
Issue
2
fYear
1996
fDate
4/1/1996 12:00:00 AM
Firstpage
65
Lastpage
70
Abstract
A centralised plot-level data fusion technique, which is based on a neural network, is presented. A self-organised feature-mapping technique, which learns from sensor observations, is used to integrate the data from several sensors with various unknown measurement accuracies. Topological neighbourhood formulation among networks for integrating data is described. Computer simulations show that neural data fusion enjoys many advantages over maximum likelihood fusion and other ad hoc fusion methods
Keywords
learning (artificial intelligence); self-organising feature maps; sensor fusion; target tracking; centralised plot-level data fusion technique; feature-mapping data fusion; multitarget tracking; neural data fusion; neural network; self-organised feature-mapping technique; sensor observations; topological neighbourhood formulation; unknown measurement accuracies;
fLanguage
English
Journal_Title
Radar, Sonar and Navigation, IEE Proceedings -
Publisher
iet
ISSN
1350-2395
Type
jour
DOI
10.1049/ip-rsn:19960138
Filename
494710
Link To Document