During the vibration process, the output of the gyroscope will add a non-zero offset small amount based on the Earth's rotational speed component, which is the output error term of the gyroscope vibration. When the gyroscope adopts two different closed-loop models, the error magnitude of the same gyroscope is different. Therefore, selecting an optimal closed-loop model while adjusting appropriate closed-loop parameters is crucial for solving the vibration problem of gyroscopes. Firstly, compare the differences and stability conditions between the two closed-loop models; Secondly, analyze the reasons for the error terms generated during the vibration process of the gyroscope and the reasons for the different sizes of error terms generated by different models; Then simulate and analyze the output of gyroscope vibration under different closed-loop models. The simulation and specific experimental results indicate that selecting an optimal closed-loop model shortens the closed-loop integration delay time of the model, and maximizes the closed-loop gain as much as possible while ensuring that there are no resonance peaks in the closed-loop amplitude frequency characteristic curve. This can reduce the output error term of the gyroscope and improve its dynamic performance.
Process initial alignment and azimuth estimation algorithm is an important technology of the land vehicle Strapdown Optical Fiber Positioning and Orientation System (SOFPOS). The initial alignment of the vehicle is easily affected by the maneuvering environment such as turning and the noise of the odometer, especially when turning sharply, the alignment accuracy of the optical fiber system will be reduced. Firstly, this paper analyzes the principle of odometer lever arm error and the measurement compensation method in the SOFPOS. A comprehensive physical model based on the longitudinal lever arm and the left and right lateral lever arms is proposed, and the odometer lever arm error model is also simulated. Then, the lever arm error is estimated by Kalman filter, and the odometer lever arm error is compensated. Finally, the compensation is applied to the initial alignment and azimuth estimation algorithm during the journey, and the experimental verification is completed by combining the hardware-in-the-loop simulation. The test results show that the alignment accuracy and positioning accuracy of the positioning and orientation system can be effectively improved by estimating and compensating the error of the odometer lever arm, and the environmental applicability of the land vehicle optical fiber positioning and orientation system can be improved.
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