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Sensors 2016, 16(6), 864; doi:10.3390/s16060864

Gyro Drift Correction for An Indirect Kalman Filter Based Sensor Fusion Driver

1
School of Computer Science and Engineering, Chung-Ang University, Seoul 156-756, Korea
2
Department of Vehicle Components, LG Electronics, Seoul 073-36, Korea
*
Author to whom correspondence should be addressed.
Received: 24 April 2016 / Revised: 7 June 2016 / Accepted: 8 June 2016 / Published: 11 June 2016
(This article belongs to the Special Issue Advances in Multi-Sensor Information Fusion: Theory and Applications)
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Abstract

Sensor fusion techniques have made a significant contribution to the success of the recently emerging mobile applications era because a variety of mobile applications operate based on multi-sensing information from the surrounding environment, such as navigation systems, fitness trackers, interactive virtual reality games, etc. For these applications, the accuracy of sensing information plays an important role to improve the user experience (UX) quality, especially with gyroscopes and accelerometers. Therefore, in this paper, we proposed a novel mechanism to resolve the gyro drift problem, which negatively affects the accuracy of orientation computations in the indirect Kalman filter based sensor fusion. Our mechanism focuses on addressing the issues of external feedback loops and non-gyro error elements contained in the state vectors of an indirect Kalman filter. Moreover, the mechanism is implemented in the device-driver layer, providing lower process latency and transparency capabilities for the upper applications. These advances are relevant to millions of legacy applications since utilizing our mechanism does not require the existing applications to be re-programmed. The experimental results show that the root mean square errors (RMSE) before and after applying our mechanism are significantly reduced from 6.3 × 10−1 to 5.3 × 10−7, respectively. View Full-Text
Keywords: sensor fusion; indirect Kalman filter; accuracy improvement; gyro drift correction sensor fusion; indirect Kalman filter; accuracy improvement; gyro drift correction
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Lee, C.-G.; Dao, N.-N.; Jang, S.; Kim, D.; Kim, Y.; Cho, S. Gyro Drift Correction for An Indirect Kalman Filter Based Sensor Fusion Driver. Sensors 2016, 16, 864.

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