Tilt Measurement with a MEMS Accelerometer Based on Kalman Filter


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Aiming at the high noise level with Micro-Electro-Mechanical System (MEMS) accelerometer, the Kalman filter algorithm is introduced to analyse its output data along with the noises. Experiments and simulations are designed to evaluate the performance and stability under static state and the response speed under dynamic state. The results indicate that the method works fast, steady and effectively with MEMS accelerometer filtering and tilt measurement.



Advanced Materials Research (Volumes 430-432)

Edited by:

Ran Chen, Dongye Sun and Wen-Pei Sung




Q. H. Ji "Tilt Measurement with a MEMS Accelerometer Based on Kalman Filter", Advanced Materials Research, Vols. 430-432, pp. 1947-1951, 2012

Online since:

January 2012





[1] Lu Poyuan, Liu Sibin. Design of Attitude Sensor Using ADIS16354 hip, CHINESE JOURNAL OF SENSORS AND ACTUATORS. 2010, 23(2): 192-195.

[2] Alison K. Brown. GPS/INS uses Low-Cost MEMS IMU[J]. A&E SYSTEMS MAGAZINE, IEEE, 2005, 20(9): 3-10.

DOI: https://doi.org/10.1109/maes.2005.1514768

[3] STMicroelectronics, LIS331DLH: MEMS digital output motion sensor ultra low-power high performance 3-axes nano, accelerometer[EB/OL]. http: /www. st. com/internet/analog/product/218132. jsp, (2009).

[4] Yu, Zhangguan, Modern control theory and Application [M]. Ha Erbing, Harbin Institute of Technology press, (2007).

[5] Greg Welch, Gary Bishop, An Introduction to the Kalman Filter[EB/OL]. http: /www. cs. unc. edu/~welch/kalman/ kalmanInrto. html, (2006).

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