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Research on improved fine alignment methods

机译:改进的精细对准方法研究

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摘要

Based on the hypothesis of small values of misalignment angles, compass alignment and linear Kalman alignment are common fine alignment methods. The algorithm of compass alignment has good robustness, but the convergence efficiency and accuracy of alignment are contradictory, which is necessary to set appropriate control parameters to reconcile. Because Kalman alignment method is based on a deterministic filtering model, the algorithm is relatively stable, but the drift of IMU (Inertial Measurement Unit) will cause the drift of the errors of misalignment angles. In order to take into account the effects of both long and short damping periods on compass alignment, the exponential finite time-varying damping period is used to improve the convergence efficiency of azimuth alignment. In order to solve the divergence of horizontal misalignment angles of Kalman precise alignment algorithm, a realtime correction algorithm of attitude matrix with full feedback of misalignment angle estimations is introduced. The simulation and turntable experiments verify the effectiveness of the improved methods.
机译:基于未对准角度小值的假设,指南针对准和线性卡尔曼对齐是常见的精细对准方法。罗盘对齐算法具有良好的鲁棒性,但对准的收敛效率和准确性是矛盾的,这是设置适当的控制参数来协调的必要条件。因为卡尔曼对齐方法基于确定性滤波模型,所以算法相对稳定,但IMU(惯性测量单元)的漂移将导致错位角度的误差。为了考虑到罗盘对准的长短阻尼周期的影响,指数有限的时变阻尼周期用于提高方位角对准的收敛效率。为了解决卡尔曼精确对准算法水平未对准角的分歧,介绍了具有全对准角度估计的完全反馈的姿态矩阵的实时校正算法。模拟和转盘实验验证了改进方法的有效性。

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