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
fDate :
9/1/1995 12:00:00 AM
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;
Journal_Title :
Control Theory and Applications, IEE Proceedings -
DOI :
10.1049/ip-cta:19952020