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A method improving the alignment accuracy of medium accuracy MEMS inertial navigation system on revolving base

机译:一种提高中精度MEMS旋转惯性导航系统对准精度的方法

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In initial alignment for a medium accuracy MEMS strapdown inertial navigation system on a stationary base, when the Kalman filtering algorithm is adopted in initial alignment, as the east gyro drift rate cannot be estimated, it yields a constant error in the estimation of the azimuth misalignment angle. To, improve the alignment accuracy, a novel alignment method on revolving mounting base is proposed. The Strong Tracking filter algorithm of extending the measured values is studied. The theory of spectral condition number is utilized to analyze the degrees of observability of states. Simulation results show that the estimation accuracy of the azimuth misalignment angle has been improved greatly through revolving the mounting base and the method proposed in this paper is efficient in initial alignment for a medium accuracy MEMS SINS.
机译:在固定基座上的中等精度MEMS捷联惯性导航系统的初始对准中,当在初始对准中采用Kalman滤波算法时,由于无法估计东陀螺仪的漂移率,因此在估计方位角未对准时会产生恒定误差角度。为了提高对准精度,提出了一种新型的旋转安装座对准方法。研究了扩展测量值的强跟踪滤波器算法。光谱条件数理论被用来分析状态的可观察度。仿真结果表明,通过旋转底座可以大大提高方位角未对准角的估计精度,并且本文提出的方法对于中等精度的MEMS SINS初始对准是有效的。

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