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Research on modeling and filtering method of atomic spin gyroscope's random drift

机译：原子自旋陀螺仪随机漂移建模与滤波方法研究

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Atomic spin gyroscope is a new kind of gyro based on quantum mechanics, with ultra-high precision, simple structure, small size, etc. Therefore, to study the characteristics of random drift for improving the accuracy of atomic spin gyro is significant. Firstly, through the analysis of the gyro static output data and preprocessing, the stationary time series gyro random error has obtained. Then established the gyro drift error model based on time series ARIMA, and test the applicability of the model through analysis of residual. Finally, through the establishment of the Kalman filter based on the model to filter out the gyro random drift, and the use of Allan variance analysis of the filtering results. The results show that the modeling and filtering method and can effectively reduce the atomic spin gyro random drift error, the angle random walk coefficient raised an order of magnitude compared with traditional ARMA modeling method, so as to effectively enhance the output accuracy of atomic spin gyro and stability of the system.
机译：原子自旋陀螺仪是一种基于量子力学的新型陀螺仪，具有超高精度，结构简单，体积小等优点。因此，研究随机漂移的特性对于提高原子自旋陀螺仪的精度具有重要意义。首先，通过对陀螺仪静态输出数据的分析和预处理，得到了静止时间序列的陀螺仪随机误差。然后建立了基于时间序列ARIMA的陀螺漂移误差模型，并通过残差分析验证了模型的适用性。最后，通过建立基于模型的卡尔曼滤波器来滤除陀螺仪的随机漂移，并利用艾伦方差分析对滤波结果进行分析。结果表明，该建模和滤波方法能够有效降低原子自旋陀螺仪的随机漂移误差，与传统的ARMA建模方法相比，角度随机游走系数提高了一个数量级，从而有效地提高了原子自旋陀螺仪的输出精度。和系统的稳定性。

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