Hybrid Kalman filter-fuzzy logic adaptive multisensor data fusion architectures

被引：32
|
作者：
Escamilla-Ambrosio, PJ [1 ]
Mort, N [1 ]
机构：
[1] Univ Bristol, Dept Aerosp Engn, Bristol BS8 1TR, Avon, England
来源：
42ND IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-6, PROCEEDINGS | 2003年
关键词：
D O I：
10.1109/CDC.2003.1272465
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：5215 / 5220
页数：6
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