Research On Signal Processing Of Fiber Optic Gyro

Fiber optic gyroscope (FOG) virtues of faster start-up, better sensitivity, more reliable, widen measurement range and digital output comparing to traditional mechanical gyros. Strapdown inertial navigation system based on FOG has been used in precision apparatus, mobile communication and national defenses area, and so forth. FOG is a kind of angular senor who has bright future in application. However, the random excursions of FOG affect output precision to a large extent. This random excursion should be compensated otherwise it will produce relative large accumulative error in navigation. To achieve this purpose, the dissertation has done several works as followings:Design data collection board and pre-process the signal of FOG. Through analyzing gyro drifting data, the frequency and time characteristics and statistical specialties are acquired. After preprocessing, the FOG signals are basically balanced and normal that can be used to establish mathematical model for compensation.Identify the noise parameters and model the drifting data by Allan Variance and time series analyses. Advanced Allan variance method was used in system identification especially for five main random error coefficients. ARMA model was employed to model mathematical models for FOG and the parameters of ARMA were introduced to Kalman filter to compensate random drifting.Finally, hardware based filter algorithms was investigated for better application. Through integrating others' experience, advanced FFT frequency analysis instrument was designed by introduce CORDIC algorithm. And also an IIR low pass filter was established by bring hardware multiplication organ and summator.