Random Error Prediction of Laser Gyroscope Based on GM(1,1) Model

Abstract

Allan variance analysis method can make static analysis, identifying static laser gyroscope random error and random error as the working environment, operation process changes, human disturbance and other factors, but it can't give dynamic characterization of random error coefficient under the static under laser gyroscope random error compensation to provide accurate basis, based on the segmented dynamic. Allan variance method is proposed to identify random error term, based on the gray GM (1, 1) prediction model using prior Allan variance analysis to identify dynamic parameters to predict subsequent coefficient of random error of laser gyro random error compensation, the test results show that the prediction model is effective and the prediction variance ratio is small, so it can predict and compensate the random error coefficient of the laser gyroscope in the same working environment.