A De-Noising Method of Acceleration Signal for Vehicle Based on Kalman Filter and Average Filter

Abstract:

A de-noising method is proposed for 3DM-GX1 accelerometer signal based on kalman filter and average filter. This method can reduce the disturbance caused by vibration of vehicle motion and sensor itself, get acceleration accurately, and have advantages of easy realization and good real-time performance. A vehicle acceleration signal model is established with real acceleration noises as simulation signals based on kalman filter and average filter. Experiments based on real vehicle acceleration signal showed that the method could reflect the detailed information effectively by filtering noise, and it is very suitable for de-noising of vehicle acceleration signals which needs real-time application. The start, stop, advance and retreat action could be identify from the acceleration signal by using the proposed de-noising method based on kalman filter and average filter.

• Periodical: Advanced Materials Research (Volumes 225-226)
• Pages: 605-608
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.225-226.605
• Online since: April 2011
• Authors: Chen Zhang, Chang Yong Xu
• Keywords: Acceleration Signal, Average Filter, De-Noising Method, Kalman Filter (KF), Vehicle

References

[1] Tan Chin—Woo, Park Sungsu．Design of gyro scope free navigation systems[C] IEEE Intelligent Transportation Systems Conference Proceedings．Oakland: IEEE, 2001: 286—291.

DOI: 10.1109/itsc.2001.948670

[2] Tan Chin—Woo, Park Sungsu．Design of accelerometer—based inertial navigation systems[J]. IEEE Transactions on Instrumentation and Measurement, 2005, 54(4): 2520—2530.

DOI: 10.1109/tim.2005.858129

[3] Wang Aiping, Wang Huinan, 1/f nosie eliminating based on wavelet analysis. Journal of Data Acquisition and Processing, 2006, 21(2): 217-221.

[4] Fu Mengyin, Deng Zhihong, ZHang Jiwei．Kalman filter theory and its applications in navigation system[M]．Beijing: Science Press, (2003).

[5] Fu Mengyin, Deng Zhihong, ZHang Jiwei．Kalman filter theory and its applications in navigation system[M]．Beijing: Science Press, 2003.

[6] Gao Yu, Zhang Jianqiu, Kalman filter with wavelet-based unknown measurement noise estimation and its application for information fusion. ACTA Electronica Sinica, 2007, 35(1): 108-111.

[7] Hua Yingchun, Zhang Jinquan. Kalman filtering method is applied to control the suspension bridge construction - steel box girder lifting phase of [J]. Road Traffic Technology, 1999, 16（2）38-41 (In Chinese).

[8] Yang Fei. Kalman filtering method in the concrete cable-stayed bridge construction control of [J]. Sichuan Building, 2008, 28（3）: 161-163 (In Chinese).

[9] WU Chunli, Li Han. Cable-stayed bridge for-cable construction control [J]. Communication Science and Technology, Jilin, 2006, 103（2）: 47-49 (In Chinese).