A Real-Time Prediction Algorithm of BDS Satellite Clock Offset Considering Phase Jumps

Author(s):  
Wenju Fu ◽  
Qin Zhang ◽  
Meng Ao ◽  
Guanwen Huang ◽  
Hairong Guo
2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Xu Yang ◽  
Qianxin Wang ◽  
Shuqiang Xue

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.


2017 ◽  
pp. 205-221 ◽  
Author(s):  
Matthias Beggiato ◽  
Timo Pech ◽  
Veit Leonhardt ◽  
Philipp Lindner ◽  
Gerd Wanielik ◽  
...  

2013 ◽  
Vol 846-847 ◽  
pp. 475-478
Author(s):  
Cui Feng Du ◽  
Wen Ming Shen ◽  
Shi Bao Jiang

The real-time prediction of micro regional market share provides decision for the analysis of micro regional marketing scheme and micro regional channel planning. More and more increasing complexion mobile network environment require real-time micro area of market share and only mastering micro regional market share can have a more comprehensive understanding of market. To solve this problem, consideration of advantages of real-time aspects of the extended Kalman filtering algorithm in predicting, we propose a real-time prediction algorithm based on the extended Kalman filter Market Share. The algorithm can be real-time prediction of mobile network market share of base station. The simulation results show that the proposed algorithm in this paper is a real-time and good prediction quality.


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