A hybrid Kalman filter-fuzzy logic architecture for multisensordata fusion
Escamilla-Ambrosio, P.J.; Mort, N.
Intelligent Control, 2001. (ISIC apos;01). Proceedings of the 2001 IEEE International Symposium on
Volume , Issue , 2001 Page(s):364 - 369
Digital Object Identifier 10.1109/ISIC.2001.971537
Summary:A novel hybrid multi-sensor data fusion (MSDF) architecture
integrating Kalman filtering and fuzzy logic techniques is explored. The
objective of the hybrid MSDF architecture is to obtain fused measurement
data that determines the parameter being measured as precisely as
possible. To reach this objective, first each measurement coming from
each sensor is fed to a fuzzy-adaptive Kalman filter (FKF), thus there
are n sensors and n FKFs working in parallel. Next, a fuzzy logic
observer (FLO) monitors the performance of each FKF. The FLO assigns a
degree of confidence, a number on the interval [0, 1], to each one of
the FKFs output. The degree of confidence indicates to what level each
FKF output reflects the true value of the measurement. Finally, a
defuzzificator obtains the fused estimated measurement based on the
confidence values. To demonstrate the effectiveness and accuracy of this
new hybrid MSDF architecture, an example with four noisy sensors is
outlined. Different defuzzification methods are explored to select the
best one for this particular application. The results show very good
performance
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