Abstract

Geographical distribution of global navigation satellite system (GNSS) ground monitoring stations affects the accuracy of satellite orbit, earth rotation parameters (ERP), and real-time satellite clock offset determination. The geometric dilution of precision (GDOP) is an important metric used to measure the uniformity of the stations distribution. However, it is difficult to find the optimal configuration with the lowest GDOP when taking the 71% ocean limitation into account, because the ground stations are hardly uniformly distributed on the whole of the Earth surface. The station distribution geometry needs to be optimized and besides the stability and observational quality of the stations should also be taken into account. Based on these considerations, a method of configuring global station tracking networks based on grid control probabilities is proposed to generate optimal configurations that approximately have the minimum GDOP. A random optimization algorithm method is proposed to perform the station selection. It is shown that an optimal subset of the total stations can be obtained in limited iterations by assigning selecting probabilities for the global stations and performing a Monte Carlo sampling. By applying the proposed algorithm for observation data of 201 International GNSS Service (IGS) stations for 3 consecutive days, an experiment of ultra-rapid orbit determination and real-time clock offset estimation is conducted. The distribution effects of stations on the products accuracy are analyzed. It shows that (1) the accuracies of GNSS ultra-rapid observed and predicted orbits and real-time clock offset achieved using the proposed algorithm are higher than those achieved with the traditional method having the drawbacks of lacking evaluation indicators and being time-consuming, corresponding to the improvements 17.15%, 19.30%, and 31.55%, respectively. Only using 30 stations selected by the proposed method, the accuracies achieved reach 2.01 cm (RMS), 4.93 cm (RMS), and 0.20 ns (STD), respectively. Using 60 stations, the accuracies are 1.47 cm, 3.50 cm, and 0.17 ns, respectively. (2) With the increasing number of stations, the accuracies of the Global Positioning System (GPS) orbit and clock offset improve continuously, but more than 60 stations, the improvement on the orbit determination becomes more gradual, while for more than 30 stations, there is no appreciable increase in the accuracy of the real-time clock offset.

Highlights

  • Nowadays, global navigation satellite system (GNSS) postprocessed and real-time precise satellite orbits and clock offsets, long-term and short-term Earth rotation parameters (ERP), interfrequency deviation parameters, and troposphere and ionosphere correction parameters, are produced using the observation data of ground monitoring stations to meet the needs of PNT users

  • After randomly selecting stations according to the grid control probability, a one-step method is used for ultra-rapid orbit determination [25] and the zerodifference method is used for real-time clock offset estimation [26]

  • A random optimization algorithm for the selection of GNSS global monitoring stations based on the selection judgment index WSDOP was proposed

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Summary

Introduction

GNSS (global navigation satellite systems) postprocessed and real-time precise satellite orbits and clock offsets, long-term and short-term Earth rotation parameters (ERP), interfrequency deviation parameters, and troposphere and ionosphere correction parameters, are produced using the observation data of ground monitoring stations to meet the needs of PNT (positioning navigation and timing) users. The international GNSS Monitoring and Assessment System (iGMAS) tracking network (http://www.igmas.org/) is developed by China to collect multi-GNSS observations and provide satellite orbit and clock, station coordinates and kinds of products for global users [6]. In the satellite orbit determination, ERP and clock offset estimation, the GDOP of the stations relative to the geocenter is calculated by taking the ground stations as the control points and the geocenter as the unknown point [7, 13, 14]. The above discussion shows optimizing the latter GDOP may improve the accuracy of ultra-rapid orbit and real-time clock offset estimation. It is shown that the proposed approach can quickly and automatically select high quality and well-distributed stations, improving the accuracy of ultra-rapid orbit determination and real-time clock offset estimation and the calculation of ERP

Station-Geocenter DOP Measuring the Uniformity of the Stations
Random Selection Algorithm Based on WSDOP
Experimental Analysis
Conclusion
Findings
Conflicts of Interest
Full Text
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