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On-Orbit Calibration Method for Redundant IMU Based on Satellite Navigation & Star Sensor Information Fusion

机译:基于卫星导航和星传感器信息融合的冗余IMU的On-Orbit校准方法

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Aiming at the long term and high-precision performance maintenance requirements of the satellite-borne four-axis redundant inertial measurement unit (IMU) in space, the satellite navigation velocity information, the attitude information provided by the star sensor and the redundant measurement output are used as references to derive the measurement model, including the star sensor installation error. Three rotation sequences of optimal observation, suboptimal observation, and under-observation are designed and compared. The Kalman filter is used to calibrate the redundant IMU in the orbit. The numerical simulation shows that all three rotation sequences can calibrate more than 91% of the constant error, which meets the requirements of the use, and the calibration accuracy of the optimal rotation sequence is the highest. The ground repeatability calibration experiment is carried out 10 times for the optimal rotation sequence. The calibration results show that the range of all the error terms is less than its threshold, illustrating that the calibration result is stable and reliable. It is a real-time calibration method for all error terms on orbit, providing a reference method for the high-precision performance maintenance of the spacecraft integrated navigation system.
机译:旨在长期和高精度的性能维护要求的卫星传播的四轴冗余惯性测量单元(IMU),卫星导航速度信息,星传感器提供的姿态信息和冗余测量输出用作引用测量模型的引用,包括星传感器安装错误。设计并比较了三个最佳观察,次优观察和观察序列的旋转序列。卡尔曼滤波器用于校准轨道中的冗余IMU。数值模拟表明,所有三个旋转序列都可以校准超过91%的恒定误差,这符合使用要求,最佳旋转序列的校准精度最高。接地重复性校准实验是为最佳旋转序列的10次进行。校准结果表明,所有误差项的范围小于其阈值,说明校准结果稳定可靠。它是轨道上所有误差项的实时校准方法,提供了用于航天器集成导航系统的高精度性能维护的参考方法。

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