Research on MEMS Gyro Random Drift Restraining Based on Simplified Sage-Husa Adaptive Filter Algorithm

Xiong Cai; An Ping Qiu; Wei Xing Qian; Qin Shi

doi:10.4028/www.scientific.net/AMR.403-408.127

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 403-408Research on MEMS Gyro Random Drift Restraining...

Research on MEMS Gyro Random Drift Restraining Based on Simplified Sage-Husa Adaptive Filter Algorithm

Abstract:

The various random noises in MEMS gyro are the main factor affecting the accuracy. In accordance with the property of its noise, traditional filtering has many shortages. If so, a simplified Sage-Husa adaptive filter algorithm is discussed. The algorithm can estimate the system process noise accurately when observation noise is known. The paper sets up ARMA model of MEMS gyro random error and processes the drift data by the filtering. The result shows that the random noise is reduce by 70％ .

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Periodical:

Advanced Materials Research (Volumes 403-408)

Pages:

127-131

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.403-408.127

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Online since:

November 2011

Authors:

Xiong Cai, An Ping Qiu, Wei Xing Qian, Qin Shi

Keywords:

ARMA Model, MEMS Gyro, Random Drift, Sage-Husa Adaptive Filter

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References

[1] Ji Xunsheng, Wang Shourong, Xu Yishen and Sheng Ping, Application of the adaptive kalman filter in the MEMS gyro signal processing, Transducer and Microsystem Technologies, vol. 25, Sep. 2001, pp.79-81.

Google Scholar

[2] Li Jie, Liu Jun, Zhang Wendong and Yang Wei, Research on Random Error compensation Methods for MEMS Gysoscope, Journal of North University of China(Natural Science Edition), vol . 30, N0. 4, 2009, pp.381-385.

Google Scholar

[3] Martin Nilsson, Kalman Filtering with Unkown Noise Covariances, In: Reglermöte 2006, 30-31 May 2006, Stockholm, Sweden.

Google Scholar

[4] Andrew P. Sage and Gary W. Husa, Algorithm for Sequential Adaptive Estimation of Prior Statistixs, Adaptive Processes(8th) Decision and Control, 1969, pp.61-70.

DOI: 10.1109/sap.1969.269927

Google Scholar

[5] Yang Peipei and Li Qing, Kalman Filtering of MEMS Gyro Based on Time-series Model, The Ninth International Conference on Electrionic Measurement & Instruments, (2009).

DOI: 10.1109/icemi.2009.5274567

Google Scholar

[6] Wu Kang, A New Type of Adaptive Kalman Filtering Algorithm and Its Application, Piezoelectrics & Acoutstooptics, vol. 31, Dec. 2009, pp.908-911.

Google Scholar

[7] Fu Mengyin, Deng Zhihong and Zhang Jiwei, The theory of Kalman filtering and Its Application in Navigation, Beijing, (2003).

Google Scholar

[8] Zhang Changyun, Approch to Adaptive Filtering Algorithm, Acta Aeronautica et Astronautica Sinica, vol. 19, Dec. 1998, pp.96-99.

Google Scholar

[9] Li Jie, , Zhang Wendong and Liu Jun, Research on the Application of the Time-Serial Analysis Based Kalman Filter in MEMS Gyroscope Random Drift Compensation, Chinese Journal of Sensors and Actuators, vol. 19, Oct. 2006, pp.2215-2219.

Google Scholar

[10] Piet M.T. Broersen and Stijn de Waele, Finite Sample Properties of ARMA Order Selection, IEEE Transactions on Instrumentation and Measurement, vol. 53, NO. 3, JUNE, (2004).

DOI: 10.1109/tim.2004.827058

Google Scholar

[11] Hou Haiying, Modeling Inertial Sensors Errors Using Allan Variance, University of Calgary, Sep. (2004).

Google Scholar