Zhang Y., Du C., Zhou Y., Chen C.
School of Instrumentation Science and Opto-electronics Engineering, Beijing University of Aeronautics and Astronautics, 100191, China; School of Information Technology, Tsinghua University, 100084, China
Abstract:
The characteristic of the output error of the geomagnetic sensor is analysed and the finite difference method is used to smooth the non-stationary data of geomagnetic sensor. Then the ARIMA model of the non-stationary data is established by using the time series analysis method. Considered the time series model as the State equation and the present moment measurement data as the measured values, this article designs the Kalman filter based on the model of ARIMA(3,2,0) to deal with the output data of the geomagnetic sensor. The result shows that the mean square error of the measurement data reduced 73.6% after filtering. The result of the raw data has proved the validity of the proposed model and filtering method. The research methods of this article can also be used for error modeling and filtering of. other kinds of sensors.. © 2010 IEEE.
Author Keywords:
ARIMA model; Geomagnetic sensor; Kalman filtering; Time series analysis
Year:
2010
Source title:
2nd International Conference on Information Science and Engineering, ICISE2010 - Proceedings
Art. No.:
5691377
Page :
6639-6641
Link:
Scorpus Link
Document Type:
Conference Paper
Source:
Scopus
Authors with affiliations:
-
Zhang, Y., School of Instrumentation Science and Opto-electronics Engineering, Beijing University of Aeronautics and Astronautics, 100191, China
-
Du, C., School of Instrumentation Science and Opto-electronics Engineering, Beijing University of Aeronautics and Astronautics, 100191, China
-
Zhou, Y., School of Instrumentation Science and Opto-electronics Engineering, Beijing University of Aeronautics and Astronautics, 100191, China
-
Chen, C., School of Information Technology, Tsinghua University, 100084, China
Download Abstract:
geo7.pdf