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http://dx.doi.org/10.6109/jkiice.2011.15.12.2511

Performance Enhancement of Attitude Estimation using Adaptive Fuzzy-Kalman Filter  

Kim, Su-Dae (부산대학교 전자전기공학과)
Baek, Gyeong-Dong (부산대학교 전자전기공학과)
Kim, Tae-Rim (현대모비스)
Kim, Sung-Shin (부산대학교 전자전기공학부)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.15, no.12, 2011 , pp. 2511-2520 More about this Journal
Abstract
This paper describes the parameter adjustment method of fuzzy membership function to improve the performance of multi-sensor fusion system using adaptive fuzzy-Kalman filter and cross-validation. The adaptive fuzzy-Kanlman filter has two input parameters, variation of accelerometer measurements and residual error of Kalman filter. The filter estimates system noise R and measurement noise Q, then changes the Kalman gain. To evaluate proposed adaptive fuzzy-Kalman filter, we make the two-axis AHRS(Attitude Heading Reference System) using fusion of an accelerometer and a gyro sensor. Then we verified its performance by comparing to NAV420CA-100 to be used in various fields of airborne, marine and land applications.
Keywords
Adaptive fuzzy-Kalman filter; Sensor fusion; Attitude Heading Reference System; Cross-validation;
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