Abstract
This paper proposes a novel fuzzy-adaptive extended Kalman filter (FAEKF) for the real-time attitude estimation of agile mobile platforms equipped with magnetic, angular rate, and gravity (MARG) sensor arrays. The filter structure employs both a quaternion-based EKF and an adaptive extension, in which novel measurement methods are used to calculate the magnitudes of system vibrations, external accelerations, and magnetic distortions. These magnitudes, as external disturbances, are incorporated into a sophisticated fuzzy inference machine, which executes fuzzy IF-THEN rules-based adaption laws to consistently modify the noise covariance matrices of the filter, thereby providing accurate and robust attitude results. A six-degrees of freedom (6 DOF) test bench is designed for filter performance evaluation, which executes various dynamic behaviors and enables measurement of the true attitude angles (ground truth) along with the raw MARG sensor data. The tuning of filter parameters is performed with numerical optimization based on the collected measurements from the test environment. A comprehensive analysis highlights that the proposed adaptive strategy significantly improves the attitude estimation quality. Moreover, the filter structure successfully rejects the effects of both slow and fast external perturbations. The FAEKF can be applied to any mobile system in which attitude estimation is necessary for localization and external disturbances greatly influence the filter accuracy.
Highlights
This paper proposes a novel fuzzy-adaptive extended Kalman filter (FAEKF) for the real-time attitude estimation of agile mobile platforms equipped with magnetic, angular rate, and gravity (MARG) sensor arrays
The attitude estimation performance of the FAEKF was evaluated on three measurements performed in the test environment (Measurements 1–3 lasted for approximately 160 s, 210 s, and 315 s, respectively)
This paper proposed a novel qAEKF structure, FAEKF, in which both new measurement techniques were developed for the calculation of external disturbance magnitudes and novel adaptation laws were implemented with fuzzy logic
Summary
Ákos Odry 1, * , Istvan Kecskes 1 , Peter Sarcevic 2 , Zoltan Vizvari 3 , Attila Toth 4. Received: 21 December 2019; Accepted: 29 January 2020 ; Published: 1 February 2020
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