Low-Cost Inertial Sensors Modeling Using Allan Variance
Micro-electromechanical system (MEMS)
accelerometers and gyroscopes are suitable for the inertial navigation
system (INS) of many applications due to low price, small
dimensions and light weight. The main disadvantage in a comparison
with classic sensors is a worse long term stability. The estimation
accuracy is mostly affected by the time-dependent growth of inertial
sensor errors, especially the stochastic errors. In order to eliminate
negative effects of these random errors, they must be accurately
modeled. In this paper, the Allan variance technique will be used in
modeling the stochastic errors of the inertial sensors. By performing
a simple operation on the entire length of data, a characteristic curve
is obtained whose inspection provides a systematic characterization
of various random errors contained in the inertial-sensor output data.
[1] J. Gao, “Development of a Precise GPS/INS/On-Board Vehicle Sensors
Integrated Vehicular Positioning System, PhD” (Book style). Thesis,
Department of Geomatics Engineering, University of Calgary, Canada,
2007.
[2] R. Hulsing, “MEMS Inertial Rate and Acceleration Sensor”, IEEE
Position Location and Navigation Symposium, pp. 169-176, Apr. 1998.
[3] IEEE “Standard Specification Format Guide and Test Procedure for
Single-Axis Interferometric Fiber Optic Gyros”, IEEE Std 952-1997
[4] J. W. Judy, “Micro electromechanical systems (MEMS): fabrication,
design and applications”, Electrical Engineering Department, University
of California, Los Angeles, 2001.
[5] D. W. Allan, “Statistics of atomic frequency standards”, Proceedings of
the IEEE 54, 2 (Feb. 1966), 221–230.
[6] N. El-Sheimy, H. Hou and X. Niu, “Analysis and Modeling of Inertial
Sensors Using Allan Variance”, IEEE Transactions On Instrumentation
And Measurement, Vol. 57, No. 1, January 2008.
[7] W Stockwell, Angle Random Walk, http://www.xbow.com.
[8] SparkFun Electronics, 9 Degrees of Freedom- Razor IMU- SEN-10736.
http://www.sparkfun.com
[1] J. Gao, “Development of a Precise GPS/INS/On-Board Vehicle Sensors
Integrated Vehicular Positioning System, PhD” (Book style). Thesis,
Department of Geomatics Engineering, University of Calgary, Canada,
2007.
[2] R. Hulsing, “MEMS Inertial Rate and Acceleration Sensor”, IEEE
Position Location and Navigation Symposium, pp. 169-176, Apr. 1998.
[3] IEEE “Standard Specification Format Guide and Test Procedure for
Single-Axis Interferometric Fiber Optic Gyros”, IEEE Std 952-1997
[4] J. W. Judy, “Micro electromechanical systems (MEMS): fabrication,
design and applications”, Electrical Engineering Department, University
of California, Los Angeles, 2001.
[5] D. W. Allan, “Statistics of atomic frequency standards”, Proceedings of
the IEEE 54, 2 (Feb. 1966), 221–230.
[6] N. El-Sheimy, H. Hou and X. Niu, “Analysis and Modeling of Inertial
Sensors Using Allan Variance”, IEEE Transactions On Instrumentation
And Measurement, Vol. 57, No. 1, January 2008.
[7] W Stockwell, Angle Random Walk, http://www.xbow.com.
[8] SparkFun Electronics, 9 Degrees of Freedom- Razor IMU- SEN-10736.
http://www.sparkfun.com
@article{"International Journal of Information, Control and Computer Sciences:69960", author = "A. A. Hussen and I. N. Jleta", title = "Low-Cost Inertial Sensors Modeling Using Allan Variance", abstract = "Micro-electromechanical system (MEMS)
accelerometers and gyroscopes are suitable for the inertial navigation
system (INS) of many applications due to low price, small
dimensions and light weight. The main disadvantage in a comparison
with classic sensors is a worse long term stability. The estimation
accuracy is mostly affected by the time-dependent growth of inertial
sensor errors, especially the stochastic errors. In order to eliminate
negative effects of these random errors, they must be accurately
modeled. In this paper, the Allan variance technique will be used in
modeling the stochastic errors of the inertial sensors. By performing
a simple operation on the entire length of data, a characteristic curve
is obtained whose inspection provides a systematic characterization
of various random errors contained in the inertial-sensor output data.", keywords = "Allan variance, accelerometer, gyroscope, stochastic
errors.", volume = "9", number = "5", pages = "1246-6", }