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An Improved ACKF/KF Initial Alignment Method for Odometer-Aided Strapdown Inertial Navigation System

机译:里程表辅助捷联惯导系统的改进ACKF / KF初始对准方法

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摘要

For a land-vehicle strapdown inertial navigation system (SINS), the problem of initial alignment with large misalignment angle in-motion needs to be solved urgently. This paper proposes an improved ACKF/KF initial alignment method for SINS aided by odometer. The SINS error equation with large misalignment angle is established first in the form of an Euler angle. The odometer/gyroscope dead reckoning (DR) error equation is deduced, which makes the observation equation linear when the position is taken as the observation of the Kalman filter. Then, based on the cubature Kalman filter, the Sage-Husa adaptive filter and the characteristics of the observation equation, an improved ACKF/KF method is proposed, which can accomplish initial alignment well in the case of unknown measurement noise. Computer simulation results show that the performance of the proposed ACKF/KF algorithm is superior to EKF, CKF and AEKF method in accuracy and stability, and the vehicle test validates its advantages.
机译:对于陆上捷联惯性导航系统(SINS),急需解决大偏心角运动中的初始对准问题。提出了一种改进的里程表辅助捷联惯导系统的ACKF / KF初始对准方法。首先以欧拉角的形式建立大偏心角的SINS误差方程。推导了里程表/陀螺仪航位推算(DR)误差方程,当将位置作为卡尔曼滤波器的观测值时,观测值方程变为线性。然后,基于库曼卡尔曼滤波器,Sage-Husa自适应滤波器和观测方程的特点,提出了一种改进的ACKF / KF方法,该方法可以在测量噪声未知的情况下很好地完成初始对准。计算机仿真结果表明,所提出的ACKF / KF算法的性能在准确性和稳定性上均优于EKF,CKF和AEKF方法,并且通过车辆测试证明了其优势。

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