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A Novel Approach Based on MEMS-Gyro's Data Deep Coupling for Determining the Centroid of Star Spot

机译:基于MEMS-陀螺仪数据深度耦合的新方法确定星点质心

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The traditional approach of star tracker for determining the centroid of spot requires enough energy and good shape, so a relatively long exposure time and stable three-axis state become necessary conditions to maintain high accuracy, these limit its update rate and dynamic performance. In view of these issues, this paper presents an approach for determining the centroid of star spot which based on MEMS-Gyro's data deep coupling, it achieves the deep fusion of the data of star tracker and MEMS-Gyro at star map level through the introduction of EKF. The trajectory predicted by using the angular velocity of three axes can be used to set the extraction window, this enhances the dynamic performance because of the accurate extraction when the satellite has angular speed. The optimal estimations of the centroid position and the drift in the output signal of MEMS-Gyro through this approach reduce the influence of noise of the detector on accuracy of the traditional approach for determining the centroid and effectively correct the output signal of MEMS-Gyro. At the end of this paper, feasibility of this approach is verified by simulation.
机译:传统的恒星跟踪仪确定光斑质心的方法需要足够的能量和良好的形状,因此相对较长的曝光时间和稳定的三轴状态成为保持高精度的必要条件,这限制了其更新速度和动态性能。针对这些问题,本文提出了一种基于MEMS-Gyro数据深度耦合的恒星点质心确定方法,通过介绍,实现了恒星跟踪器和MEMS-Gyro数据在星图层面的深度融合。 EKF。通过使用三个轴的角速度预测的轨迹可用于设置提取窗口,这将增强动态性能,因为当卫星具有角速度时可以精确提取。通过该方法对质心位置和MEMS-陀螺仪的输出信号中的漂移的最佳估计减小了检测器的噪声对确定质心的传统方法的准确性的影响,并有效地校正了MEMS-Gyro的输出信号。最后,通过仿真验证了该方法的可行性。

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