USING ALLAN VARIANCE TO DETERMINE THE CALIBRATION MODEL OF INERTIAL SENSORS FOR GPS/INS INTEGRATION

In this research, Allan Variance analysis is used to identify the stochastic error sources existing in inertial sensors and to determine the corresponding noise parameters. According to the noise parameters, the power spectral density (PSD) function of the stochastic error sources can be determined. The differential equation descriptions for individual stochastic errors are then derived for two circumstances: rational spectral PSD and non-rational spectral PSD. Then, a unified calibration model in the form of differential equation for multiple stochastic errors is derived. By incorporating the unified calibration model into the traditional INS error equation, the Kalman Filter for GPS/INS integration is augmented. At last, the actual test data are processed to elaborate and exemplify the approach proposed.