Fuzzy Adaptive Kalman Filtering for INS/GPS data fusion

被引：96

作者：

Sasiadek, JZ ^{[1
]}

Wang, Q ^{[1
]}

Zeremba, MB ^{[1
]}

机构：

[1] Carleton Univ, Dept Mech & Aerosp Engn, Ottawa, ON K1S 5B6, Canada

来源：

PROCEEDINGS OF THE 2000 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL | 2000年

关键词：

Kalman filtering; fuzzy logic control; GPS/INS; navigation; sensor fusion;

D O I：

10.1109/ISIC.2000.882920

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a novel method for sensor fusion based on Adaptive Fuzzy Kalman Filtering. The method is applied in fusing position signals from Global Positioning System (GPS) and Inertial Navigation System (MS) for autonomous mobile vehicles. The presented method has been validated in a 3-D environment and is of particular importance for guidance, navigation, and control of flying vehicles. The Extended Kalman Filter (EKF) and the noise characteristics are modified using the Fuzzy Logic Adaptive System, and compared with the performance of a regular EKF. It is demonstrated that the Fuzzy Adaptive Kalman Filter gives better results, in terms of accuracy, than the EKF.

引用

页码：181 / 186

页数：6

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