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Dual-EKF-Based Real-Time Celestial Navigation for Lunar Rover

机译：基于双EKF的月球漫游者实时天体导航

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摘要

A key requirement of lunar rover autonomous navigation is to acquire state information accurately in real-time during its motion and set up a gradual parameter-based nonlinear kinematics model for the rover. In this paper, we propose a dual-extended-Kalman-filter- (dual-EKF-) based realtime celestial navigation (RCN) method. The proposed method considers the rover position and velocity on the lunar surface as the system parameters and establishes a constant velocity (CV) model. In addition, the attitude quaternion is considered as the system state, and the quaternion differential equation is established as the state equation, which incorporates the output of angular rate gyroscope. Therefore, the measurement equation can be established with sun direction vector from the sun sensor and speed observation from the speedometer. The gyro continuous output ensures the algorithm real-time operation. Finally, we use the dual-EKF method to solve the system equations. Simulation results show that the proposed method can acquire the rover position and heading information in real time and greatly improve the navigation accuracy. Our method overcomes the disadvantage of the cumulative error in inertial navigation.
机译：月球车自主导航的一个关键要求是在其运动过程中实时准确地获取状态信息，并为月球车建立基于渐进参数的非线性运动学模型。在本文中，我们提出了一种基于双扩展卡尔曼滤波（双EKF）的实时天体导航（RCN）方法。提出的方法将月球车在月球表面的位置和速度作为系统参数，建立了恒速模型。另外，将姿态四元数视为系统状态，并将四元数微分方程建立为状态方程，其中包含角速率陀螺仪的​​输出。因此，可以利用来自太阳传感器的太阳方向矢量和来自速度计的速度观测来建立测量方程。陀螺仪的连续输出确保算法实时运行。最后，我们使用双重EKF方法求解系统方程。仿真结果表明，所提方法能够实时获取漫游者的位置和航向信息，大大提高了导航精度。我们的方法克服了惯性导航中累积误差的缺点。

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  • 来源
    《Mathematical Problems in Engineering》 |2012年第5期|p.17.1-17.16|共16页
  • 作者

    Li Xie; Peng Yang; Thomas Yang; Ming Li;

  • 作者单位

    Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China,Zhejiang Provincial Key Laboratory of Information Network Technology, Hangzhou 310027, China;

    Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China,Zhejiang Provincial Key Laboratory of Information Network Technology, Hangzhou 310027, China;

    The Department of Electrical, Computer, Software, and Systems Engineering, Embry-Riddle Aeronautical University, Daytona Beach, FL 32114, USA;

    School of Information Science and Technology, East China Normal University, Shanghai 200241, China;

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