Application of Least Squares-Support Vector Machine in system-level temperature compensation of ring laser gyroscope

Characterization of a fiber optic gyroscope in a measurement while drilling system with the dynamic Allan variance

To improve the dynamic random error compensation accuracy of the Micro Electro Mechanical System (MEMS) gyroscope at different angular rates, an adaptive filtering approach based on the dynamic variance model was proposed. In this paper, experimental data were utilized to fit the dynamic variance model which describes the nonlinear mapping relations between the MEMS gyroscope output data variance and the input angular rate. After that, the dynamic variance model was applied to online adjustment of the Kalman Filter measurement noise coefficients. The proposed approach suppressed the interference from the angular rate in the filtering results. Dynamic random errors were better estimated and reduced. Turntable experiment results indicated that the adaptive filtering approach compensated for the MEMS gyroscope dynamic random error effectively both in the constant angular rate condition and the continuous changing angular rate condition, thus achieving adaptive dynamic random error compensation.

An Adaptive Filtering Approach Based on the Dynamic Variance Model for Reducing MEMS Gyroscope Random Error

The stability of a fiber optic gyroscope (FOG) in measurement while drilling (MWD) could vary with time because of changing temperature, high vibration, and sudden power failure. The dynamic Allan variance (DAVAR) is a sliding version of the Allan variance. It is a practical tool that could represent the non-stationary behavior of the gyroscope signal. Since the normal DAVAR takes too long to deal with long time series, a fast DAVAR algorithm has been developed to accelerate the computation speed. However, both the normal DAVAR algorithm and the fast algorithm become invalid for discontinuous time series. What is worse, the FOG-based MWD underground often keeps working for several days; the gyro data collected aboveground is not only very time-consuming, but also sometimes discontinuous in the timeline. In this article, on the basis of the fast algorithm for DAVAR, we make a further advance in the fast algorithm (improved fast DAVAR) to extend the fast DAVAR to discontinuous time series. The improved fast DAVAR and the normal DAVAR are used to responsively characterize two sets of simulation data. The simulation results show that when the length of the time series is short, the improved fast DAVAR saves 78.93% of calculation time. When the length of the time series is long ( 6 × 10 5 samples), the improved fast DAVAR reduces calculation time by 97.09%. Another set of simulation data with missing data is characterized by the improved fast DAVAR. Its simulation results prove that the improved fast DAVAR could successfully deal with discontinuous data. In the end, a vibration experiment with FOGs-based MWD has been implemented to validate the good performance of the improved fast DAVAR. The results of the experience testify that the improved fast DAVAR not only shortens computation time, but could also analyze discontinuous time series.

Application of Fast Dynamic Allan Variance for the Characterization of FOGs-Based Measurement While Drilling

According to the Kalman filter equations, an error distribution formula of the error of state estimation is deduced, which includes the influence of initial state variance matrix, system noise matrix and measurement noise matrix. A new definition of degree of state observability, the computing method, and the criteria to judge the level of state observability are also proposed. The new concept of degree of observability can be used to visualize the state observability of the Kalman filter over time. Combined with the error distribution analysis method, the main factors affecting the error of state estimation are given, which can be used to optimize the design of the filter and reduce the filter errors. The proposed algorithm is applied to the initial alignment simulation and the analysis of the strapdown inertial navigation system (SINS), and the results are proved to be correct and valid.

魏国 Wei Guo

Papers

Research on Stochastic Errors of Dithered Ring Laser Gyroscope Based on Dynamic Allan Variance

Vehicle integrated navigation based on laser Doppler velocimeter

Observability Analysis of Fixed Position Initial Alignment of Strapdown Inertial Navigation System

Application of High-Accuracy Laser Doppler Velocimeter in Self-Contained Land Navigation System