Analysis Of Dynamic Performance Of Fiber Optic Gyroscope

Fiber optic gyroscope (FOG) is widely applied in strapdown inertial navigation system (SINS), and its performance largely determines the precision of SINS. At home and abroad, lots of researches on the performance of FOG are reported in the state of rest or uniform motion, i.e., the static properties of FOG, however, the study on the performance of FOG in the state of angular acceleration motion is less, i.e., the dynamic performance of FOG. In this paper, study the error theory of FOG under the dynamic conditions, test methods, analysis of test results and the improvement methods of performance systematically.SINS fix directly with the carrier, which are always under angular acceleration state in the actual movement. Therefore, the performance of FOG under angular acceleration state determines the accuracy of SINS.The error model of FOG under the dynamic condition is established, basing on the analysis of FOG system model and response characteristics under angular acceleration motion. The influence of FOG stability conditions, structural parameters, signal processing cycle as well as the external environment on the dynamic performance of FOG are discussed. In theory, the affect mechanism of light average wavelength and feedback channel gain on the structural parameters are analyzed; the influence mechanism of the step height signal and the output signal filtering on the signal processing cycle are discussed. Simulation results indicate that the error model of FOG under the dynamic conditions is accurate and reliable.To evaluate the dynamic performance of FOG reasonably, the three-axis inertial test turntable is chosen to test the dynamic performance of FOG. The input angular velocity signal of FOG changes according to sine law. The test principle and procedures are presented. In this paper, three methods are presented to determine the reference value in dynamic test, which are location divided difference, separated period discretization theory curve and transform formula method. Separated period discretization theory curve and transform formula method are suitable among these.The accuracy of three-axis turntable is one of the key factors that constrain the precision of FOG test results. Based on the characteristics of output signals under the sway states, use of the Pisarenko spectrum decomposition method is preferred for identifying the output signals of turntable, which include the amplitude distortion, frequency distortion and the component harmonics. In this paper, the standard deviations of turntable errors are compared and analyzed to identify the credibility. Moreover, the distortion laws are analyzed under two conditions:different turntable frames the same sway conditions and identical turntable frame the different sway conditions. The results indicate that the Pisarenko spectrum decomposition method is applicable to identify the sinusoidal signal distortion of turntable.Based on the wavelet natures of multiresolution analysis and spatial localization, db5wavelet is choosed to fiter the noise of turntable trajectory for avoiding it to pass in the reference signal of dynamic test. The results indicate that the filtering effect of wavelet is satisfactory and it improves the accuracy of the dynamic test results of FOG.The time delay between the reference signal and the actual signal in dynamic test is analyzed and compensated using time delay estimation theory. Related operation is done to estimate and further compensate the time delay between the two signals, based on signals and noises, noises and noises are irrelevant in the test. The results indicate that time delay has a greater impact on test results and the dynamic error after compensation is in accordance with the actual situation.In order to study the dynamic performance of FOG better, it is proposed that the dynamic error which is obtained by test of FOG is analyzed by dynamic Allan variance. According to the principle of window function of dynamic Allan variance method, the analysis results of dynamic error are discussed under the different window length conditions. Furthermore, a kind of single sway movement and two kinds of composite sway movement are analyzed by dynamic Allan variance method and their results are provided. There is fluctuating variation of variance in analysis figures, by which the various non-stationary factors in the dynamic error such as mutation and periodic variation are accurately reflected and the different sway states hidded in the dynamic errors are clearly identified. Both the theoretical analysis and experimental results indicate that the dynamic Allan variance method is very applicable to analyze the dynamic performance of FOG.The dynamic Allan variance is an effective method for analyzing non-stationary signal. However, it has defects in noise identification:power leakage and single quantification. Therefore, window function combination method is introduced for their improvements as well as two-dimensional expression of noise value. They are used for analysis and quantitative measurement of various noise terms in the FOG dynamic error. Based on the dynamic error resolution of FOG, rectangular window is applied to analyze low&intermediate frequency noise, while hanning window does high-frequency noise. According to the principle of DAVAR, the noise variation laws with the numbers of sampling point are obtained, namely, two-dimensional expression of noise value. The experimental results indicate that window function combination method satisfies the identification requirements of noise in different frequency ranges and reduces power leakage; moreover, the change characteristics of every noise item in the dynamic error are accurately reflected by the two-dimensional expression of noise value.The design idea of normal PID controller is applied in the dynamic error controller of FOG to improve its dynamic performance; moreover, a novel dynamic controller structure is designed basing on the error characteristics of FOG under dynamic state. The former is implemented by the combination of design idea of normal PID with the control idea of FOG, i.e. implemented by the inner control model of FOG. For the later (the novel one), the differential link is set before the output signal, which make the output signal and feedback signal to predict in advance; meanwhile, a low-pass filter is set after the differential link to suppress the high frequency interference brought by the differential link. The novel control structure can not only decrease the control amount and avoid the calculation of control error, but also allows the output to track the input and reflects the input change. Both the controllers are realized through writing VHDL language in the digital signal processing chip FPGA of FOG. The test results indicate that both the dynamic error controllers can significantly improve the FOG dynamic performance, furthermore, the novel dynamic error controller, i.e. the dynamic error controller basing on the error characteristic of FOG under dynamic condition, has better error control performance.