Autonomous Orbit Determination System of Navigation Satellite Based on Spaceborne GPS Technology

Li Yang, Haote Ruan, Yunhan Zhang
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引用次数: 1

Abstract

In recent years, many low-orbit satellites have been widely used in the field of scientific research and national defense in China. In order to meet the demand of high-precision satellite orbit in China’s space, surveying and mapping, and other related fields, navigation satellites are of great significance. The UKF (unscented Kalman filter) method is applied to space targets’ spaceborne GPS autonomous orbit determination. In this paper, the UKF algorithm based on UT transformation is mainly introduced. In view of the situation that the system noise variance matrix is unknown or the dynamic model is not accurate, an adaptive UKF filtering algorithm is proposed. Simulation experiments are carried out with CHAMP satellite GPS data, and the results show that the filtering accuracy and stability are improved, which proves the algorithm’s effectiveness. The experimental results show that the Helmert variance component estimation considering the dynamics model can solve the problem of reasonable weight determination of BDS/GPS observations and effectively weaken the influence of coarse error and improve the accuracy of orbit determination. The accuracy of autonomous orbit determination by spaceborne BDS/GPS is 1.19 m and 2.35 mm/s, respectively.
基于星载GPS技术的导航卫星自主定轨系统
近年来,许多低轨道卫星在中国的科研和国防领域得到了广泛的应用。为了满足中国航天、测绘等相关领域对高精度卫星轨道的需求,导航卫星具有重要意义。将UKF (unscented卡尔曼滤波)方法应用于空间目标的星载GPS自主定轨。本文主要介绍了基于UT变换的UKF算法。针对系统噪声方差矩阵未知或动态模型不准确的情况,提出了一种自适应UKF滤波算法。利用CHAMP卫星的GPS数据进行了仿真实验,结果表明,该算法的滤波精度和稳定性得到了提高,证明了算法的有效性。实验结果表明,考虑动力学模型的Helmert方差分量估计可以解决BDS/GPS观测值的合理定权问题,有效地减弱了粗误差的影响,提高了定轨精度。星载北斗/GPS自主定轨精度分别为1.19 m和2.35 mm/s。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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