Impact of sampling interval on variance components of epoch-wise residual error in relative GPS positioning: A case study of a 40-km-long baseline

Anđić, Darko

doi:10.1016/j.geog.2021.05.001

Cited by 5 publications

(3 citation statements)

References 14 publications

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“…Figure 1. The concept of the method applied herein (adapted from Figure 6.3.1 in Anđić, 2019b) then one can establish the second and the fourth , c s ξ moment for those effects as follows (…”

Section: Var(mentioning

confidence: 99%

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Considering Variances of Quasi-Random Effects in Relative GPS Positioning Performed During Daytime and Nighttime Periods – A Novel Two-Stage Approach

Anđić¹

2021

Geodesy and Cartography

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In this paper, a new two-stage approach, involving an integral treatement of all quasi-random effects limiting the accuracy of relative GPS positioning and the method of moments to obtain final variance components regarding the effects of short-term (“far-field”) multipath (factor b), joint action of long-term (“near-field”) multipath and receiver antenna phase center offset and variations (factor a1), as well as joint action of tropospheric and ionospheric refraction (factor a2), is presented. In the study, GPS data collected on five baselines were used. Variance components of the quasirandom effects were obtained for the three relative GPS coordinates (e, n and u) using individually monthly datsets including daytime- and those including nighttime-wise ambiguity-fixed baseline solutions. The related results show that statistically significant inequality exists when comparing corresponding variances obtained for daytime and nighttime periods. It turned out that the following standard deviation estimates intervals are present (by the coordinates e, n and u, respectively): (a) daytime period: 3.3–6.9, 4.6–9.0 and 9.1–20.3 mm (factor b); 1.5–4.7, 1.9–7.0 and 3.4–21.9 mm (factor 1a ); 0.0116– 0.3282, 0.0103–0.2365 and 0.1222–0.7818 mm/km (factor a2); (b) nighttime period: 3.2–4.9, 4.7–7.3 and 8.4–15.4 mm (factor b); 0.8–3.8, 2.1–5.0 and 3.1–15.8 mm (factor a1); 0.0118–0.2734, 0.0097–0.2289 and 0.0752–0.6315 mm/km (factor a2).

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Section: Var(mentioning

confidence: 99%

“…But, in each of them these effects were treated individually and a reader can be referred to the recent ones, such as, e.g. Hu et al (2015), Deng et al (2016), Elsobeiey and El-Diasty (2016), Jadviščok et al (2016), Klos et al (2018), Zhou et al (2018), Anđić, (2019b), Han et al (2019), Juni and Rózsa (2019), Kallio et al (2019).…”

Section: Introductionmentioning

confidence: 99%

Considering Variances of Quasi-Random Effects in Relative GPS Positioning Performed During Daytime and Nighttime Periods – A Novel Two-Stage Approach

Anđić¹

2021

Geodesy and Cartography

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“…As we all know, a large amount of the free electrons exists in the Earth's ionosphere. Serving as the significant region of the Earth's near space, the ionospheric delay is an important error source in satellite PNT services, which can cause the delay of several meters to several hundred meters in the GNSS signal transmission [1][2][3][4][5]. With the rapid development of the GNSS, it has been the most important tool for ionospheric monitoring and correction due to its advantages of all-weather global coverage and high temporal and spatial resolutions.…”

Section: Introductionmentioning

confidence: 99%

Three Dual-Frequency Precise Point Positioning Models for the Ionospheric Modeling and Satellite Pseudorange Observable-Specific Signal Bias Estimation

Jin

2021

Remote Sensing

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Global Navigation Satellite System (GNSS) Precise Point Positioning (PPP) enables the estimation the ionospheric vertical total electron content (VTEC) as well as the by-product of the satellite Pseudorange observable-specific signal bias (OSB). The single-frequency PPP models, with the ionosphere-float and ionosphere-free approaches in ionospheric studies, have recently been discussed by the authors. However, the multi-frequency observations can improve the performances of the ionospheric research compared with the single-frequency approaches. This paper presents three dual-frequency PPP approaches using the BeiDou Navigation Satellite System (BDS) B1I/B3I observations to investigate ionospheric activities. Datasets collected from the globally distributed stations are used to evaluate the performance of the ionospheric modeling with the ionospheric single- and multi-layer mapping functions (MFs), respectively. The characteristics of the estimated ionospheric VTEC and BDS satellite pseudorange OSB are both analyzed. The results indicated that the three dual-frequency PPP models could all be applied to the ionospheric studies, among which the dual-frequency ionosphere-float PPP model exhibits the best performance. The three dual-frequency PPP models all possess the capacity for ionospheric applications in the GNSS community.

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Extracting ionospheric phase scintillation indicator from GNSS observations with 30-s sampling interval in the high-latitude region

Zhao

Zhang

et al. 2023

GPS Solut

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Impact of sampling interval on variance components of epoch-wise residual error in relative GPS positioning: A case study of a 40-km-long baseline

Cited by 5 publications

References 14 publications

Considering Variances of Quasi-Random Effects in Relative GPS Positioning Performed During Daytime and Nighttime Periods – A Novel Two-Stage Approach

Considering Variances of Quasi-Random Effects in Relative GPS Positioning Performed During Daytime and Nighttime Periods – A Novel Two-Stage Approach

Three Dual-Frequency Precise Point Positioning Models for the Ionospheric Modeling and Satellite Pseudorange Observable-Specific Signal Bias Estimation

Extracting ionospheric phase scintillation indicator from GNSS observations with 30-s sampling interval in the high-latitude region

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