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Vol. 156, Issue 9, September 2013, pp. 81-88




Using BP Neural Network and Kalman Filter to Signal Processing of MEMS Inertial Sensors
1 Wenxian XIAO, 2 Hao ZHANG, 1 Xiaoqin MA

1 Henan Institute of Science and Technology, Henan Xinxiang, 453003, China

2 Dept. of Computer Science and Technology, Henan Mechanical and Electrical Engineering College, Henan Xinxiang 453003, China
Tel.: 13849382972
E-mail: wenxianxiaoedu@163.com


Received: 3 July 2013   /Accepted: 25 August 2013   /Published: 30 September 2013

Digital Sensors and Sensor Sysstems


Abstract: The paper put forward using BP neural network and Kalman filter to signal processing of MEMS inertial sensors. This paper uses Kalman filter value for information fusion of gyroscope and accelerometer, and the attitude angle is accurate. The state and observation equation of attitude angle measuring system with characteristic of BP neural network, and the design of the Kalman filter is simple and gyroscope measurement information data fusion, the preparation of the corresponding MATLAB program Kalman filter is designed. Through the simulation results of the image, this method can compensate the zero drift of gyroscope, improves the measurement precision of the attitude angle.


Keywords: BP neural network, Kalman filter, Inertial sensors, MATLAB.


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