Abstract
A simplified and improved attitude estimation algorithm is put forward, for the problems from the multi-rotor UAV in noise statistical characteristics unknown and time-varying, vibration as the main disturbance source, and high-frequent dynamic changes of the attitude angles. A simplified adaptive Kalman filter algorithm is designed for multi-sensor information fusion. With the attitude angle variance of the real-time dynamic calculation by the gyro and the accelerometer, the system noise variance and the measurement noise variance are estimated, so as to solve the unknown about the noise statistical characteristics, and to prevent the filter divergence. The flight experiment shows that the algorithm can guarantee the accuracy and the stability of the attitude angle estimation. The root-mean-square errors of the pitch and roll angles which are estimated by the simplified algorithm are 2.922° and 1.713°. The accuracy of the algorithm can meet the demands for the autonomous flight of the multi-rotor UAV.
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Acknowledgments
In this paper, the research was sponsored by the National Natural Science Foundation of China [No. 11372309 and No. 61304017], Science and Technology Development Plan Key Project of Jilin Province [No.20150204074GX], Science and Technology Special Fund Project of Provincial Academy Cooperation [No. 2014SYHZ0004].
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Zhang, X., Bai, Y., Xu, Z., Wang, R. (2015). Attitude Estimation of the Multi-rotor UAV Based on Simplified Adaptive Kalman Filter Algorithm. In: Deng, Z., Li, H. (eds) Proceedings of the 2015 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 336. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46469-4_23
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DOI: https://doi.org/10.1007/978-3-662-46469-4_23
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