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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惯性导航系统对准精度对旋转基座的对准精度

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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:在初始准确态MEMS型惯性导航系统上的初始对准中,当初始对准中采用Kalman滤波算法时,由于无法估计东陀螺漂移速率,因此在方位角估计中产生恒定的误差角度。为了提高对准精度,提出了一种关于旋转安装基座的新型对准方法。研究了扩展测量值的强跟踪滤波器算法。光谱条件数量的理论用于分析状态的可观察性。仿真结果表明,通过旋转安装基座,估计方位角不对角度的估计精度已经大大提高,本文提出的方法在初始准确态MEMS SINS中有效。

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