印度导航星座(NavIC)卫星统计定轨算法:面向NavIC接收机的扩展星历技术

IF 0.7 Q4 ASTRONOMY & ASTROPHYSICS
T. V. Ramanathan, R. A. Chipade
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引用次数: 2

摘要

摘要星历对于全球导航卫星系统(GNSS)用户接收机中的卫星定位至关重要。导航数据和星历表参数的获取在偏远地区以及具有挑战性的环境中都很困难。在没有导航数据的情况下,统计轨道确定技术可以帮助预测轨道参数。本研究是在NavIC星座卫星没有导航数据的情况下生成轨道参数和预测卫星位置的解决方案的第一步。轨道确定算法利用单站导航数据预测卫星位置。研究了影响NavIC星座卫星轨道的扰动,并提出了一种基于扰动力模型的NavIC卫星轨道扰动算法。使用扩展卡尔曼滤波器(EKF)来处理扰动力的非线性动力学模型,并使用地面站到地球中心的距离作为测量来求解测量方程。使用单站导航数据预测卫星轨道长达1小时。1小时后,在地球同步轨道和地球静止轨道上观察到NavIC卫星的均方根误差(RMSE)分别为12.59 m和13.03 m。用于评估所提出的轨道预测EKF算法拟合优度的Kolmogorov-Smirnov检验被发现在1%的显著性水平上是显著的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Statistical Orbit Determination Algorithm for Satellites in Indian Navigation Constellation (NavIC): Towards Extended Ephemeris Technology for NavIC Receiver
Abstract Ephemerides are essential for the satellite positioning in Global Navigation Satellite Systems (GNSS) user receivers. Acquisition of navigation data and ephemeris parameters are difficult in remote areas as well as in challenging environments. Statistical orbit determination techniques can help to predict the orbital parameters in the absence of navigation data. The present study is a first step towards the solution for generating orbital parameters and predicting the satellite positions in the absence of navigation data for satellites in NavIC constellation. The orbit determination algorithm predicted the satellite position using single station navigation data. The perturbations affecting the satellite orbits in NavIC constellation were also studied and an algorithm using perturbation force models is proposed for the satellites in NavIC constellation. Extended Kalman Filter (EKF) was used to address the non-linear dynamics model of the perturbation forces and distance of the ground station from the centre of Earth was used as measurement to solve the measurement equation. The satellite orbits were predicted up to 1 hour using the single station navigation data. The root mean square error (RMSE) of 12.59 m and 13.03 m were observed for NavIC satellites in Geosynchronous and Geostationary orbits, respectively, after 1 hour. The Kolmogorov-Smirnov test used to assess the goodness of fit of the proposed EKF algorithm for orbit prediction was found to be significant at 1% level of significance.
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CiteScore
1.00
自引率
11.10%
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