Title :
Implementation of sensor selection and fusion using fuzzy logic
Author :
Lee, M. F Ricky ; Stanley, Kevin ; Wu, Q. M Jonathan
Author_Institution :
Nat. Res. Council, Vancouver, BC, Canada
Abstract :
Different sensors may contain degrees of uncertainty and may be only reliable in particular situations, therefore sensor fusion and validation can be critical in complex redundant systems. This paper proposed a generic fuzzy logic algorithm for validation and fusion of uncertain sensor data. The system degrades marginal sensor data elegantly, while still removing obviously questionable data. Sensor data is represented as Gaussian curves. The sensor fusion problem is presented as determining a fused mean and standard deviation for the Gaussian of the output abstract sensor. Four variants of the fuzzy sensor fusion and validation system are presented and examined
Keywords :
fuzzy logic; redundancy; sensor fusion; Gaussian curves; complex redundant systems; fuzzy sensor fusion; generic fuzzy logic; marginal sensor data; redundant sensor systems; sensor fusion; Bayesian methods; Councils; Degradation; Fuzzy logic; Fuzzy systems; Internal combustion engines; Prototypes; Sensor fusion; Sensor systems; Uncertainty;
Conference_Titel :
IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-7078-3
DOI :
10.1109/NAFIPS.2001.944273