Hybrid Kalman Filter-Fuzzy Logic Adaptive Multisensor Data Fusion Architectures

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Abstract

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.
Original languageAmerican English
Pages5215-5220
Number of pages4692
DOIs
StatePublished - 1 Dec 2003
Externally publishedYes
EventProceedings of the IEEE Conference on Decision and Control -
Duration: 8 Feb 2015 → …

Conference

ConferenceProceedings of the IEEE Conference on Decision and Control
Period8/02/15 → …

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Escamilla-Ambrosio, P. J., & Mort, N. (2003). Hybrid Kalman Filter-Fuzzy Logic Adaptive Multisensor Data Fusion Architectures. 5215-5220. Paper presented at Proceedings of the IEEE Conference on Decision and Control, . https://doi.org/10.1109/CDC.2003.1272465