TY - GEN
T1 - Hybrid Kalman Filter-Fuzzy Logic Adaptive Multisensor Data Fusion Architectures
AU - Escamilla-Ambrosio, P. Jorge
AU - Mort, Neil
PY - 2003
Y1 - 2003
N2 - In this work the recently developed fuzzy logic-based adaptive Kalman filter (FL-AKF) is used to build adaptive centralized, decentralized, and federated Kalman filters for Adaptive MultiSensor Data Fusion (AMSDF). The adaptation carried out is in the sense of adaptively adjusting the measurement noise covariance matrix of each local FL-AKF to fit the actual statistics of the noise profiles present in the incoming measured data. A fuzzy inference system (FIS) based on a covariance-matching technique is used as the adaptation mechanism. The effectiveness and accuracy of the proposed AMSDF approaches is demonstrated in a simulated example.
AB - In this work the recently developed fuzzy logic-based adaptive Kalman filter (FL-AKF) is used to build adaptive centralized, decentralized, and federated Kalman filters for Adaptive MultiSensor Data Fusion (AMSDF). The adaptation carried out is in the sense of adaptively adjusting the measurement noise covariance matrix of each local FL-AKF to fit the actual statistics of the noise profiles present in the incoming measured data. A fuzzy inference system (FIS) based on a covariance-matching technique is used as the adaptation mechanism. The effectiveness and accuracy of the proposed AMSDF approaches is demonstrated in a simulated example.
UR - http://www.scopus.com/inward/record.url?scp=1542289895&partnerID=8YFLogxK
U2 - 10.1109/CDC.2003.1272465
DO - 10.1109/CDC.2003.1272465
M3 - Contribución a la conferencia
AN - SCOPUS:1542289895
SN - 0780379241
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 5215
EP - 5220
BT - Proceedings of the IEEE Conference on Decision and Control
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 42nd IEEE Conference on Decision and Control
Y2 - 9 December 2003 through 12 December 2003
ER -