Statistical Models of Inertial Sensors and Integral Error Bounds
Date of Original Version
Inertial sensors such as gyroscopes and accelerometers are important components of inertial measurement units (IMUs). Sensor output signals are corrupted by additive noise plus a random drift component. This drift component, also called bias, is modeled using different types of random processes. This chapter considers the random components that are useful for modeling modern tactical-graded MEMS sensors. These components contribute to errors in the first and second integrals of the sensor output. The main contribution of this chapter is the derivation of a statistical bound on the magnitude of the error in the integral of a sensor signal due to noise and drift. This bound is a simple function of the Allan variance of a sensor.
STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics and Health
Vaccaro, Richard J., and Ahmed S. Zaki. "Statistical Models of Inertial Sensors and Integral Error Bounds." STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics and Health , (2018): 143-160. doi:10.1007/978-3-319-95117-1_9.