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提出一种适用于低轨道卫星的自主导航方法。与以往采用星光角距作为观测量的方法不同,该方法利用卫星平台中常见的星敏感器和地磁敏感器确定卫星实时轨道参数;通过对星敏感器的观测数据进行适当转换,将卫星位置单位矢量观测方程转换为线性化方程;对地磁场强度与轨道高度的关系进行拟合,利用磁强计观测数据求取地心距;采用拉格朗日差值算法确定卫星初轨,为滤波器提供初值。由于二体轨道动力学模型的一阶线性化近似引入的系统模型误差影响了滤波器性能,而一阶导数函数值的线性组合可替代高阶导数的函数值,并降低计算量,所以本文在扩展KALMAN滤波器的设计过程中,对状态方程进行了高阶线性化处理,从而提高了滤波器状态方程的离散化精度。最后,用仿真实验验证了这种低轨卫星轨道确定方法的有效性与实用性。
An autonomous navigation method suitable for low orbit satellites is proposed. Different from the previous method of using the angular celestial distance as the observational method, this method uses the star sensor and the geomagnetic sensor which are common in the satellite platform to determine the orbital real-time orbit parameters of the satellite. By properly converting the satellite sensor observation data, the satellite position unit The vector observation equation is transformed into a linearized equation; the relationship between the geomagnetic field intensity and the orbit height is fitted; the geocentric distance is obtained by using the magnetometer observation data; the Lagrange difference algorithm is used to determine the satellite orbit; Provide initial value Since the systematic model errors introduced by the first-order linearization approximation of two-body orbital dynamics model affect the performance of the filter, and the linear combination of the first-order derivative function values can replace the function values of the higher-order derivatives and reduce the computational complexity, In the process of designing the extended KALMAN filter, the state equation is linearized at high order, which improves the discretization accuracy of the filter’s state equation. Finally, the validity and practicability of the orbit determination method for LEO satellites are verified by simulation experiments.