Lang Anqi, Jiang Yu
State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace Engineering, Xi'an Jiaotong University, Xi'an 710049, China.
State Key Laboratory for Space-System Operation and Control, Xi'an Satellite Control Center, Xi'an 710049, China.
Sensors (Basel). 2025 Jun 30;25(13):4079. doi: 10.3390/s25134079.
Orbit determination for non-cooperative low Earth orbit (LEO) objects undergoing continuous low-thrust maneuvers remains a significant challenge, particularly for large satellite constellations like Starlink. This paper presents a method that integrates the unscented transformation into a batch filtering framework with an optimized rho-minimum sigma points sampling strategy. The proposed approach uses a reduced dynamics model that considers Earth's non-spherical gravity and models the combined effects of low-thrust and atmospheric drag as an equivalent along-track acceleration. Numerical simulations under different measurement noise levels, initial state uncertainties, and across multiple satellites confirm the method's reliable convergence and favorable accuracy, even in the absence of prior knowledge of the along-track acceleration. The method consistently converges within 10 iterations and achieves 24 h position predictions with root mean square errors of less than 3 km under realistic noise conditions. Additional validation using a higher-fidelity model that explicitly accounts for atmospheric drag demonstrates improved accuracy and robustness. The proposed method can provide accurate orbit knowledge for space situational awareness associated with continuously maneuvering Starlink satellites.
对于进行连续低推力机动的非合作低地球轨道（LEO）物体的轨道确定仍然是一项重大挑战，特别是对于像星链这样的大型卫星星座。本文提出了一种将无迹变换集成到具有优化的rho最小西格玛点采样策略的批处理滤波框架中的方法。所提出的方法使用了一个简化动力学模型，该模型考虑了地球的非球形引力，并将低推力和大气阻力的综合影响建模为等效的沿轨道加速度。在不同测量噪声水平、初始状态不确定性以及多颗卫星的情况下进行的数值模拟证实了该方法的可靠收敛性和良好的精度，即使在没有沿轨道加速度先验知识的情况下也是如此。该方法在10次迭代内始终收敛，并且在实际噪声条件下实现了24小时位置预测，均方根误差小于3公里。使用明确考虑大气阻力的更高保真模型进行的额外验证表明精度和鲁棒性得到了提高。所提出的方法可以为与连续机动的星链卫星相关的空间态势感知提供准确的轨道知识。
