Research On The Fiber Optic Gyroscope Signal Processing And Temperature Compensation

Fiber optic gyro (FOG) is a new solid-state inertial measurement sensors based onSagnac effect, because of the advantages of its compact structure, high precision, stronganti-interference ability, short starting time, long life, overload, etc., make the FOG hasvery broad prospects for development; In this paper，we combine the experience ofprevious studies on fiber optic gyroscope, designing taken the FPGA as the core processorthe digital double closed-loop interferometric fiber optic gyroscope system, and the mainresearch contents include the selection of digital closed-loop FOG signal detection scheme,system hardware and software implementation, and the off-line temperature errorcompensation. The main innovative research work of this paper can be summarized asfollows:Firstly, this paper provides an overview of the technical characteristics and domesticand international development and application prospects of the fiber optic gyroscope.Taking the interferometric fiber optic gyroscope (IFOG) as the study object, introducing thebasic principle of FOG-Sagnac effect, focusing on the analysis of the signal detectionscheme interferometric fiber optic gyroscope, and designing the digital double close loopcontrol scheme to compensate the modulation gain error brought by the Y waveguideintegrated optical devices temperature changes.Secondly, this paper after in-depth comparative analysis the advantages anddisadvantages of the square wave bias modulation scheme and double squrare wavemodulation scheme, choosing the double square wave modulation and demodulationscheme which has the better inhibition effect of the cross interference. Then according tothe FOG interference signal characteristics and signal detection system design requirements,completing the main components selection of hardware circuit, the circuit design and PCBboard welding, then using hardware description language to complete the design ofsoftware system, and testing the soft and hardware system.At last, this paper introduces the basic principle of particle swarm optimization (PSO)and chaotic particle swarm optimization (CPSO) algorithm, through Matlab simulationcomparative analysises the performance advantages of chaotic particle swarm optimizationalgorithm than the general particle swarm optimization algorithm, then gives the trainingmethod of BP neural network based on chaos particle Swarm optimization, and using the BP neural network based on chaotic particle swarm optimization algorithm to offlinecompensating the fiber optic gyro temperature error. The compensation results show thatthe CPSO trained neural network model can accurately fitting the trend of gyro bias andscale-factor changed with temperature, and can greatly reduces the FOG’s angular rateerror.