Research On Random Error Analysis And Signal Processing Of Fiber Optic Gyroscope

Opto-Electronic stabilization platform as a device being isolated from external rotations in inertial space, is widely used in military and civilian neighborhood. The photoelectric stabilized platform of gyroscope is the core component of photoelectric stable platform, it is used to measure the carrier angular motion in the inertial space. Its precision directly affect the stability accuracy of the system, especially in the fine tracking applications, its performance directly affects the precision of LOS stabilization. Currently, stable platform mainly used in high-precision, small size, high cost of digital closed-loop interferometric fiber optic gyroscopes.Since foreign export restrictions on high-precision fiber optic gyro, coupled with our existing fiber optic gyro accuracy level can not meet the demand for high-precision applications, signal processing is used to enhance the accuracy of the gyroscopes before their outputs are fed into the stabilized platform control system.In this paper, the signal analysis method use to identify and quantify the random error of digital closed-loop interferometric fiber optic gyroscope, and the method of signal processing is used to reduce the random error of fiber optic gyroscope. First, in-depth study of the basic principles of fiber optic gyroscope, learn about the presence in the FOG output signal of the random error term. Use Allan variance analysis from a static point of view to identify and quantify FOG five major errors: Quantization noise, Bias stability, Angle random walk, Angular rate random walk, Speed ramp. Dynamic Allan variance analysis is used to analyze the dynamic characteristics of random error of fiber optic gyroscope, which provides a basis for random error compensation of fiber optic gyroscope. According to the particularity of the output signal of fiber optic gyro, the mathematical model of random error ARMA is established by using time series modeling method. The combination of optical fiber gyro output data of the random error of ARMA model and Kalman signal processing algorithm for optical fiber gyro output data for dynamic noise reduction processing.This article proposed from two aspects: static and dynamic evaluation of the performance of optical fiber gyro, and establish the mathematical model of fiber optic gyro error. The random error of ARMA model is transformed into equivalent state space model, using the extension state dimension Kalman real time filtering processing of fiber optic gyro output data. The research of signal analysis and processing method on disturbance platform experiment, the experimental results show that the signal to analysis method can effectively evaluate the performance of the fiber optic gyro, filtering algorithm can effectively improve the measurement precision of fiberoptic gyroscope, reduce the random error of fiber optic gyroscope on the influence of the stabilized platform.