Least‐squares collocation modelling of regional ionospheric TEC for accelerating real‐time single‐frequency PPP convergence

Gong, Yangzhao; Cai, Changqun; Dai, Wujiao; Zhu, Jianjun

doi:10.1049/iet-rsn.2018.5504

Cited by 7 publications

(3 citation statements)

References 35 publications

(46 reference statements)

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“…For single-frequency GNSS observations, the ionospheric delay error is a key factor to determine the positioning performance. In the MSDQ-PPP, the slant ionospheric delay is estimated as an unknown parameter, and simultaneously the GIM product is introduced as a virtual observation, which is assigned with a proper weight to strengthen the observation model (Gong et al., 2019; Wang et al., 2020). Since the satellite hardware delay biases cannot be eliminated, the satellite differential code bias (DCB) products provided by the Chinese Academy of Sciences (CAS) are used to correct the hardware delay biases (Guo et al., 2015).…”

Section: Methodology and Processing Strategymentioning

confidence: 99%

A mixed single- and dual-frequency quad-constellation GNSS precise point positioning approach on Xiaomi Mi8 smartphones

Cai

2022

J. Navigation

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The high-precision global navigation satellite system (GNSS) positioning technique on smartphones has been attracting increasing interest in recent years. However, the low-cost GNSS chip and linearly polarised antenna embedded inside smartphones result in data lack and quality degradation, which hinders the high-precision GNSS positioning on smartphones. In this study, a mixed single- and dual-frequency quad-constellation precise point positioning (MSDQ-PPP) model is proposed to improve the positioning performance on smartphones by taking advantage of all available GNSS observations. Static and kinematic tests were made using a Xiaomi Mi8 smartphone to fully assess the MSDQ-PPP performance with comparisons to single-frequency PPP (SF-PPP) and dual-frequency PPP (DF-PPP) models. The static test results show that the MSDQ-PPP can reach an accuracy level of 0⋅39 m and 0⋅50 m in the horizontal and vertical directions with a convergence time of less than 10 min in most sessions. The MSDQ-PPP improves the positioning accuracy by 53% and 31% over the DF-PPP in the horizontal and vertical directions, respectively. In contrast to the SF-PPP, the positioning accuracy and convergence time improvement can reach 62% and 90% in the horizontal direction, respectively. In the kinematic test, the MSDQ-PPP achieves an accuracy of 0⋅7 m and 1⋅5 m in the horizontal and vertical directions, respectively. The accuracy improvement rates reach 78% and 76% over the DF-PPP, and 13% and 38% over the SF-PPP, respectively. Both static and kinematic MSDQ-PPP tests indicate significantly enhanced positioning performance.

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Section: Methodology and Processing Strategymentioning

confidence: 99%

A mixed single- and dual-frequency quad-constellation GNSS precise point positioning approach on Xiaomi Mi8 smartphones

Cai

2022

J. Navigation

Self Cite

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“…The commonly used fitting function models include the spherical harmonic function model [15], the trigonometric series model [16], and the polynomial fitting model (PFM). Among them, the PFM is more widely used due to its easy implementation [17]. It models the STEC on a single layer as a function of the longitude and latitude differences of the reference stations and the center point of the modeled area.…”

Section: Introductionmentioning

confidence: 99%

A Two-Step Regional Ionospheric Modeling Approach for PPP-RTK

Xu,

Cai,

Pan

et al. 2024

Sensors

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In the precise point positioning/real-time kinematic (PPP-RTK) technique, high-precision ionospheric delay correction information is an important prerequisite for rapid PPP convergence. The commonly used ionospheric modeling approaches in the PPP-RTKs only take the trend term of the ionospheric total electron content (TEC) variations into account. As a result, the residual ionospheric delay still affects the positioning solutions. In this study, we propose a two-step regional ionospheric modeling approach that involves combining a polynomial fitting model (PFM) and a Kriging interpolation (KI) model. In the first step, a polynomial fitting method is used to model the trend term of the ionospheric TEC variations. In the second step, a KI method is used to compensate for the residual term of the ionospheric TEC variations. Datasets collected from continuously operating reference stations (CORSs) in Hunan Province, China, are used to validate the PFM/KI method by comparing with a single PFM method and a combined PFM and inverse distance weighting interpolation (IDWI) method. The experimental results show that the two-step PFM/KI modeled ionospheric delay achieves an average root mean square (RMS) error of 1.8 cm, which is improved by about 48% and 23% when compared with the PFM and PFM/IDWI methods, respectively. Regarding the positioning performance, the PPP-RTK with the PFM/KI method takes an average of 1.8 min or 4.0 min to converge to a positioning accuracy of 1.3 cm or 2.5 cm in the horizontal and vertical directions, respectively. The convergence times are decreased by about 18% and 14% in the horizontal direction and 9% and 5% in the vertical direction over the PFM and the PFM/IDWI methods, respectively.

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“…In the tsunami detection, the gravity waves generated by the tsunami can engender the ionospheric disturbances in the E and F regions. Meanwhile, ionospheric disturbances can be studied using the real‐time total electron content measurement which is estimated by the geometry‐free combination TDCP method [14, 15]. In the airborne gravimetry, the Kin‐VADASE method [16] is modified to measure the velocity of the aircraft.…”

Section: Introductionmentioning

confidence: 99%

GNSS real‐time instantaneous velocimetry based on moving‐window polynomial modelling

Zhang

Chang

Chen

et al. 2020

IET Radar, Sonar & Navigation

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Least‐squares collocation modelling of regional ionospheric TEC for accelerating real‐time single‐frequency PPP convergence

Cited by 7 publications

References 35 publications

A mixed single- and dual-frequency quad-constellation GNSS precise point positioning approach on Xiaomi Mi8 smartphones

A mixed single- and dual-frequency quad-constellation GNSS precise point positioning approach on Xiaomi Mi8 smartphones

A Two-Step Regional Ionospheric Modeling Approach for PPP-RTK

GNSS real‐time instantaneous velocimetry based on moving‐window polynomial modelling

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