Pseudo-stochastic orbit modeling techniques for low-Earth orbiters
Pseudo-stochastic orbit modeling techniques for low-Earth orbiters
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DOI：
10.1007/s00190-006-0029-9
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发表时间：
2006-04-01
影响因子：
4.4
通讯作者：
Beutler, G
中科院分区：
文献类型：
--
作者：
Jäggi, A;Hugentobler, U;Beutler, G
地球的非球形质量分布和大气阻力对极低地球轨道卫星（LEO）造成最强的扰动。在利用GPS数据进行动态精密定轨（POD）时，通常采用重力加速度和非重力加速度模型，但也有可能在没有动力学信息的情况下，利用GPS精密单点定位来确定低轨卫星的位置。我们使用的LEO POD，它结合了GPS观测的几何强度与力模型的减少动态技术，并研究不同的伪随机轨道参数化，如瞬时速度变化（脉冲），分段恒定加速度，和连续分段线性加速度的性能。在全球定位系统观测的标准最小二乘调整过程中估计这种经验轨道参数以及其他有关参数，力求在计算低地轨道轨道时达到最高精度。我们使用的CHAMP卫星的程序，并发现，轨道可以通过独立的SLR测量在3.2厘米RMS的水平进行验证。与独立的加速度计数据的验证显示，在95%的水平，沿轨道方向的相关性。正如预期的那样，经验参数在一定程度上弥补了动态模型中的缺陷。我们分析了伪随机参数的能力，用于导出力场的错误建模部分的信息，并发现证据表明，如果伪随机参数的数量足够大，则所得到的轨道可以用于恢复力场参数。基于模拟的结果表明，基于加速度的轨道的重力场恢复比基于脉冲的轨道的性能明显更好，如果每30秒设置一次无约束的加速度，其质量可与直接估计相媲美。
The Earth's non-spherical mass distribution and atmospheric drag cause the strongest perturbations on very low-Earth orbiting satellites (LEOs). Models of gravitational and non-gravitational accelerations are utilized in dynamic precise orbit determination (POD) with GPS data, but it is also possible to derive LEO positions based on GPS precise point positioning without dynamical information. We use the reduced-dynamic technique for LEO POD, which combines the geometric strength of the GPS observations with the force models, and investigate the performance of different pseudo-stochastic orbit parametrizations, such as instantaneous velocity changes (pulses), piecewise constant accelerations, and continuous piecewise linear accelerations. The estimation of such empirical orbit parameters in a standard least-squares adjustment process of GPS observations, together with other relevant parameters, strives for the highest precision in the computation of LEO trajectories. We used the procedures for the CHAMP satellite and found that the orbits may be validated by means of independent SLR measurements at the level of 3.2 cm RMS. Validations with independent accelerometer data revealed correlations at the level of 95% in the along-track direction. As expected, the empirical parameters compensate to a certain extent for deficiencies in the dynamic models. We analyzed the capability of pseudo-stochastic parameters for deriving information about the mismodeled part of the force field and found evidence that the resulting orbits may be used to recover force field parameters, if the number of pseudo-stochastic parameters is large enough. Results based on simulations showed a significantly better performance of acceleration-based orbits for gravity field recovery than for pulse-based orbits, with a quality comparable to a direct estimation if unconstrained accelerations are set up every 30 s.