DAVAR method for random noise signal process of FOG based on optimal window

Allan variance method can not recognize the signal nonstationary of Fiber Optic Gyro (FOG). Dynamic Allan variance (DAVAR) is proposed to get the nonstationary characteristics for FOG, and a dynamic Quantitative Description for the major noise figure is applied. By theoretical analysis and experimental comparison, a random signal DAVAR analysis method based on optimal window is proposed for FOG. Analyzing the static data and dynamic data of FOG using the above method, the results show that the change process of the FOG major noise figures can be reflected accurately, and the recognition accuracy of the FOG noise figures is improved. The exper imental data show that DAVAR method based on Optimal Window can be used for FOG signal stability analysis.Allan variance method can not recognize the signal nonstationary of Fiber Optic Gyro (FOG). Dynamic Allan variance (DAVAR) is proposed to get the nonstationary characteristics for FOG, and a dynamic Quantitative Description for the major noise figure is applied. By theoretical analysis and experimental comparison, a random signal DAVAR analysis method based on optimal window is proposed for FOG. Analyzing the static data and dynamic data of FOG using the above method, the results show that the change process of the FOG major noise figures can be reflected accurately, and the recognition accuracy of the FOG noise figures is improved. The exper imental data show that DAVAR method based on Optimal Window can be used for FOG signal stability analysis.