Evaluation and analysis of real-time precise orbits and clocks products from different IGS analysis centers

Zhang, Liang; Yang, Huazhong; Gao, Yang; Yao, Yibin; Xu, Chaoqian

doi:10.1016/j.asr.2018.03.029

Cited by 60 publications

(32 citation statements)

References 24 publications

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“…The positive effect of the accuracy improvement is better for the clock offset than for the orbit. As a whole, the accuracies achieved with the probability method can reach the same level as IGS RTS products [33].…”

Section: ( ) Multiday Station Selection Experiments Of Grid Controlmentioning

confidence: 72%

“…The nominal accuracies of IGU observed orbits and clocks are 3.00 cm and 3.00 ns, respectively (http://www.igs.org/products). Zhang et al [33] performed an evaluation and analysis of RTS orbits and clocks products from different IGS analysis centers. The results showed that the RMSE of satellite orbit ranged from 3.80 cm to 7.50 cm for different RTS products.…”

Section: Data Processing and Experimental Analysismentioning

confidence: 99%

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Random Optimization Algorithm on GNSS Monitoring Stations Selection for Ultra‐Rapid Orbit Determination and Real‐Time Satellite Clock Offset Estimation

Yang

Wang

Xue

2019

Mathematical Problems in Engineering

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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.

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Section: ( ) Multiday Station Selection Experiments Of Grid Controlmentioning

confidence: 72%

Section: Data Processing and Experimental Analysismentioning

confidence: 99%

Random Optimization Algorithm on GNSS Monitoring Stations Selection for Ultra‐Rapid Orbit Determination and Real‐Time Satellite Clock Offset Estimation

Yang

Wang

Xue

2019

Mathematical Problems in Engineering

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“…The process of the RT-PPP time and frequency transfer using the clock model is shown in Figure 2. It mainly includes two parts, as follows: (1) We obtain the observations from the receiver (connected to their time and frequency generator, a 1 PPS signal and a 5/10 MHz frequency signal), broadcast ephemeris and state space representation (SSR) corrections from IGS/ACs [25][26][27]. (2) If the data is not interrupted, it will go directly to RT-PPP processing to calculate the difference between the local time UTC (i) and the reference time (ref).…”

Section: The Clock Modelmentioning

confidence: 99%

An Approach to a Clock Offsets Model for Real-Time PPP Time and Frequency Transfer During Data Discontinuity

Qin

Pei

2019

Applied Sciences

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To resolve the dilemma in any post-processing strategy, i.e., the difficulty of monitoring the real-time time and frequency signals in a timely manner, real-time GPS time and the frequency transfer have recently become trending topics. Unfortunately, data interruption occurs when conducting real-time time transfer, sometimes from unexpected reasons. In this study, to ensure the stability and precision of real-time time transfer, an adaptive prediction model and a between-epoch constraint receiver clock model are applied as the mathematic models. The purpose of prediction is to solve the ambiguity from re-convergence when the data reappear. Moreover, compared to the conventional method, the between-epoch constraint receiver clock model is employed in this study to consider the correlation of epoch-wise clock parameters to avoid wasting useful information. The simulation data and real data are compared to verify the performance of the new approach. The simulation data for 165 days are designed with random daily interruptions of 10, 30, 60 and 90 min. Real data from 12 days is captured from the incomplete data in routine observation records. Ignoring the simulation data and real data, the investigation of six stations shows that the results with the between-epoch constraint receiver clock model were smoother than those with a white noise model. With an adaptive prediction model and the between-epoch constraint receiver clock model, the simulation results illustrate that the average root mean squares (RMS) values of all the stations are significantly reduced, i.e., by 66.03% from 0.43 to 0.14 ns, by 64.91% from 0.44 to 0.15 ns, by 57.47% from 0.43 to 0.18 ns, and by 51.67% from 0.44 to 0.21 ns for the 10, 30, 60 and 90 min data interruptions, respectively. The stability of all the stations is improved by at least 50%. The improvement increases to 100% for short-term stability. The real results show that the stability of four links is boosted by at least 5%. The model proposed in this paper is more effective in producing short-term stability than long-term stability.

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“…With the great efforts of international GNSS service (IGS) and international GNSS monitoring and assessment service (iGMAS), several types of precise orbit and clock products for BDS satellites are provided to satisfy various positioning demands with different accuracies [5][6][7][8]. Among these products, the ultra-rapid product is generated for possible real-time applications by calculating orbits and clocks over the next 24 h. Although the orbit product with an about five centimeter uncertainty can be neglected, the precision of predicted clocks cannot satisfy the requirement of real-time precise point positioning (RT-PPP) [6,9]. Therefore, improving the accuracies of predicted clocks is of considerable interest in order to make RT-PPP workable.…”

Section: Introductionmentioning

confidence: 99%

Improving Clock Prediction Algorithm for BDS-2/3 Satellites Based on LS-SVM Method

Zhou

Liu

et al. 2019

Remote Sensing

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The satellite clock prediction is crucial to support real-time global satellite precise positioning services. Currently, the clock prediction for the Chinese BeiDou navigation satellite system (BDS) is still challenging to satisfy the precise positioning applications. Based on the exploration of existing prediction models, an improved model combing the spectrum analysis model (SAM) and the least-squares support-vector machine (LS-SVM) is proposed especially for BDS-2/3 satellites. Considering satellite-specific characteristics, the parameters of the LS-SVM method are optimized satellite by satellite, including input length, regularization and kernel parameters. The improved model is evaluated by comparing the predicted clocks of existing methods and the improved model. The bias of the predicted clock offsets are within ±1.0 ns for most medium Earth orbits (MEOs) over three hours employing the improved model, which is better than that of the existing methods and can be applied for several real-time precise positioning applications. The predicted clock offsets are further evaluated by applying clock corrections to precise point positioning (PPP) in both static and kinematic modes for 10 international GNSS service (IGS) Multi-GNSS Experiment (MGEX) stations, including five stations in the Asia-Pacific region. According to the practical engineering experience, 2 dm and 5 dm are defined for static and kinematic PPP, respectively, as a convergence threshold. Then, in the static PPP, the improved model is demonstrated to be effective, and positioning accuracies of some stations obtain more than 15% improvements on average for each direction, which enables them to get sub-decimeter positioning, especially in the Asia-Pacific region. In the kinematic PPP, the improved model performs much better than the others in terms of both the convergence time and the positioning accuracy. The convergence time can be shortened from 1.0 h to below 0.5 h, while the positioning accuracies are enhanced by 16.3%, 10.8%, and 18.9% on average in east, north, and up direction, respectively.

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Evaluation and analysis of real-time precise orbits and clocks products from different IGS analysis centers

Cited by 60 publications

References 24 publications

Random Optimization Algorithm on GNSS Monitoring Stations Selection for Ultra‐Rapid Orbit Determination and Real‐Time Satellite Clock Offset Estimation

Random Optimization Algorithm on GNSS Monitoring Stations Selection for Ultra‐Rapid Orbit Determination and Real‐Time Satellite Clock Offset Estimation

An Approach to a Clock Offsets Model for Real-Time PPP Time and Frequency Transfer During Data Discontinuity

Improving Clock Prediction Algorithm for BDS-2/3 Satellites Based on LS-SVM Method

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