DocumentCode
1001744
Title
Centralised integration of multisensor noisy and fuzzy data
Author
Hong, L. ; Wang, G.-J.
Author_Institution
Dept. of Electr. Eng., Wright State Univ., Dayton, OH, USA
Volume
142
Issue
5
fYear
1995
fDate
9/1/1995 12:00:00 AM
Firstpage
459
Lastpage
465
Abstract
The paper discusses centralised integration of multisensor noisy and fuzzy data, which employs both Kalman filtering and fuzzy arithmetic. Because of the property of fuzzy arithmetic, the parameter fuzziness in a system under extended operation will increase without limit and finally reach an unacceptable range. Hong and Wang adopted a new compression technique to solve this problem. This paper extends their work on single sensor noisy and fuzzy data filtering to multisensor noisy and fuzzy data filtering. An example is given to illustrate the effectiveness of the algorithm presented
Keywords
Kalman filters; data compression; filtering theory; fuzzy set theory; sensor fusion; Kalman filtering; centralised integration; data compression; fuzzy arithmetic; fuzzy data; multisensor noisy data;
fLanguage
English
Journal_Title
Control Theory and Applications, IEE Proceedings -
Publisher
iet
ISSN
1350-2379
Type
jour
DOI
10.1049/ip-cta:19952020
Filename
468420
Link To Document