自主GNSS卫星轨道预测中的潜在力模型

Sakari Rautalin, S. Ali-Löytty, R. Piché
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引用次数: 6

摘要

在本文中,我们提出了一种提高自主GNSS卫星轨道预测精度的方法,该方法包括潜在力,即利用广播星历数据估计的力。自主预测的目的是减少单机定位装置的首次定位时间。我们的轨道模型包括重力和太阳辐射力以及初始状态估计算法。我们提出了潜在力的状态空间模型,这是为了纠正我们的力模型的不足,我们描述了潜在力是如何被纳入我们的预测算法的一部分。提出了一种利用多星历估计潜在力的新算法,显著提高了GPS、GLONASS和北斗系统的轨道预测精度。例如,对于GPS卫星的7天预测,SISRE的68%分位数,即定位精度估计,降低了37.1%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Latent force models in autonomous GNSS satellite orbit prediction
In this paper, we present a method for improving autonomous GNSS satellite orbit prediction accuracy by including latent forces, i.e. forces that are estimated with broadcast ephemeris data. The purpose of autonomous prediction is to reduce the Time to First Fix of a stand-alone positioning device. Our orbit model includes gravity and solar radiation forces and initial state estimation algorithm. We present a state-space model for the latent forces, which are meant to correct the deficiencies of our force model, and we describe how latent forces are incorporated as a part of our prediction algorithm. Using a novel algorithm, where multiple ephemerides are used to estimate the latent forces, the orbit prediction accuracy for GPS, GLONASS and Beidou is significantly improved. For example, for 7-day prediction of GPS satellites, the 68% quantile of SISRE, which is an estimate of positioning accuracy, reduced 37.1%.
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