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Correction published on 3 November 2017, see Sensors 2017, 17(11), 2530.

Open AccessArticle
Sensors 2017, 17(9), 2146; doi:10.3390/s17092146

A New Quaternion-Based Kalman Filter for Real-Time Attitude Estimation Using the Two-Step Geometrically-Intuitive Correction Algorithm

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1
Key Laboratory of instrumentation Science & Dynamic Measurement, Ministry of Education, North University of China, Taiyuan 030051, China
2
National Key Laboratory for Electronic Measurement Technology, North University of China, Taiyuan 030051, China
*
Author to whom correspondence should be addressed.
Received: 9 August 2017 / Revised: 6 September 2017 / Accepted: 11 September 2017 / Published: 19 September 2017
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [6355 KB, uploaded 8 November 2017]   |  

Abstract

In order to reduce the computational complexity, and improve the pitch/roll estimation accuracy of the low-cost attitude heading reference system (AHRS) under conditions of magnetic-distortion, a novel linear Kalman filter, suitable for nonlinear attitude estimation, is proposed in this paper. The new algorithm is the combination of two-step geometrically-intuitive correction (TGIC) and the Kalman filter. In the proposed algorithm, the sequential two-step geometrically-intuitive correction scheme is used to make the current estimation of pitch/roll immune to magnetic distortion. Meanwhile, the TGIC produces a computed quaternion input for the Kalman filter, which avoids the linearization error of measurement equations and reduces the computational complexity. Several experiments have been carried out to validate the performance of the filter design. The results demonstrate that the mean time consumption and the root mean square error (RMSE) of pitch/roll estimation under magnetic disturbances are reduced by 45.9% and 33.8%, respectively, when compared with a standard filter. In addition, the proposed filter is applicable for attitude estimation under various dynamic conditions. View Full-Text
Keywords: AHRS; attitude estimation; magnetic distortion; two-step geometrically intuitive correction (TGIC); Kalman filter AHRS; attitude estimation; magnetic distortion; two-step geometrically intuitive correction (TGIC); Kalman filter
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Feng, K.; Li, J.; Zhang, X.; Shen, C.; Bi, Y.; Zheng, T.; Liu, J. A New Quaternion-Based Kalman Filter for Real-Time Attitude Estimation Using the Two-Step Geometrically-Intuitive Correction Algorithm. Sensors 2017, 17, 2146.

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