The Method of Earth Rotation Parameter Determination Using GNSS Observations and Precision Analysis

Wang, Qianxin; Dang, Yamin; Xu, Tianhe

doi:10.1007/978-3-642-37398-5_24

Cited by 11 publications

(9 citation statements)

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“…The orthogonality and uniformity conditions in (6) indicate that the total observational information will be optimally allocated to the eight quadrants in three-dimensional space; thus, the optimality of the ground stations can be achieved at least for the ERP determination, c.f. Wang et al [4] As is well known, the geometry of the station distribution is only one of impact factors affecting the GNSS products, e.g., some of stations improve the geometric configuration obviously, but their quality may be poor, leading to bad GNSS products. For this, we further introduce the following weighted station-geocenter DOP as…”

Section: Station-geocenter Dop Measuring the Uniformity Of The Stationsmentioning

confidence: 99%

“…, 90. The WSDOP values in ascending order and the corresponding SDOP values according to (4) for each group of stations are obtained. After selecting the lists of stations corresponding to the first 10 and last 10 values of each group of WSDOP values, ultra-rapid orbit determination and real-time clock offset estimation are performed, respectively.…”

Section: ( ) Single-day Station Selection Experiments Of the Grid Controlmentioning

confidence: 99%

“…However, for larger than 25 tracking stations networks, the accuracy was not observed to significantly further increase with the number of stations. Wang et al [4] point out that the geometric accuracy of ERP estimation is highest when the station coordinates vectors are orthogonal, and the accuracy is proportional to the squared root of the number of stations. Nowadays, there are more than 500 global monitoring stations of the International GNSS Service (IGS).…”

Section: Introductionmentioning

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: Station-geocenter Dop Measuring the Uniformity Of The Stationsmentioning

confidence: 99%

Section: ( ) Single-day Station Selection Experiments Of the Grid Controlmentioning

confidence: 99%

Section: Introductionmentioning

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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“…For the case of two stations, the best ERP are computed when the vectors formed from these two stations to the geocenter are orthogonal. However, for three stations, the best ERP are computed when the vectors of three stations to the geocenter are mutually orthogonal [11].…”

Section: T Z T H X T Y T Z T X T Y T Z Tmentioning

confidence: 99%

Impact of Geometry Distribution of GNSS Station and Satellite on ERP Determination Precision

He¹,

Wang²,

Hu³

et al. 2018

dtetr

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Abstract. To directly describe the relationship between the ERP determination precision and the geometry distribution of GNSS station and satellite, a new dilution of precision factor (DOP) is suggested and named as EDOP. According to the hypothesis of smaller EDOP value corresponding to higher ERP solution precision, the minimum requirement and optimal distribution conditions of station and satellite are obtained to estimate the ERP using GNSS technology. The minimum requirement of ERP solvable are that there are at least two stations and two satellites, and they are not in the same plane. The optimal distribution conditions of station and satellite are that 1) the precision of ERP estimation is highest, when the stations are evenly distributed at the intersection of a sphere and a cone with a cone angle of 109.4712°, and the rotations of the distribution or additions of multiple distributions are still optimal; 2) the higher coverage density of satellites, the better precision of ERP estimation. To verify the above deductions, two experimental schemes are designed and real GNSS data is processed. The results show that 1) the hypothesis of EDOP is correct, where smaller EDOP value corresponds to better precision of ERP solution; 2) the linear functions can be adopted to describe the relation between the ERP solution precision and the EDOP value; 3) the solution precision of pole motion is more sensitive to EDOP variation than that of UT1-UTC.

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“…No matter in the initial stage or in the maturity stage, the optimal design and optimal utilization of GNSS stations are always very important for the parameters estimation precision and the computational efficiency. Therefore, many investigations have been performed to tackle this problem [Wang, Dang and Xu (2013); Zhang, Zhang, Huang et al (2015); Hu, Wang, Wang et al (2017)]. During the early development of GPS, the optimization of GPS global tracking network design was studied widely for various purposes [Delikaraoglou (1985); Bernd and Wolfgang (1988); Stephen and Willy (1989)].…”

Section: Introductionmentioning

confidence: 99%

A Method for Rapidly Determining the Optimal Distribution Locations of GNSS Stations for Orbit and ERP Measurement Based on Map Grid Zooming and Genetic Algorithm

Wang

Mao

2018

CMES

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Designing the optimal distribution of Global Navigation Satellite System (GNSS) ground stations is crucial for determining the satellite orbit, satellite clock and Earth Rotation Parameters (ERP) at a desired precision using a limited number of stations. In this work, a new criterion for the optimal GNSS station distribution for orbit and ERP determination is proposed, named the minimum Orbit and ERP Dilution of Precision Factor (OEDOP) criterion. To quickly identify the specific station locations for the optimal station distribution on a map, a method for the rapid determination of the selected station locations is developed, which is based on the map grid zooming and heuristic technique. Using the minimum OEDOP criterion and the proposed method for the rapid determination of optimal station locations, an optimal or near-optimal station distribution scheme for 17 newly built BeiDou Navigation Satellite System (BDS) global tracking stations is suggested. To verify the proposed criterion and method, real GNSS data are processed. The results show that the minimum OEDOP criterion is valid, as the smaller the value of OEDOP, the better the precision of the satellite orbit and ERP determination. Relative to the exhaustive method, the proposed method significantly improves the computational efficiency of the optimal station location determination. In the case of 3 newly built stations, the computational efficiency of the proposed method is 35 times greater than that of the exhaustive method. As the number of stations increases, the improvement in the computational efficiency becomes increasingly obvious.

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The Method of Earth Rotation Parameter Determination Using GNSS Observations and Precision Analysis

Cited by 11 publications

References 1 publication

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

Impact of Geometry Distribution of GNSS Station and Satellite on ERP Determination Precision

A Method for Rapidly Determining the Optimal Distribution Locations of GNSS Stations for Orbit and ERP Measurement Based on Map Grid Zooming and Genetic Algorithm

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