Assessment of BeiDou differential code bias variations from multi-GNSS  network observations

Jin, Shuanggen; Jin, Rui; Li, D.

doi:10.5194/angeo-34-259-2016

Cited by 79 publications

(34 citation statements)

References 34 publications

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“…A good TEC coverage from GPS dual-frequency observation is available around the M w = 7.8 Haida Gwaii earthquake, especially in the southeast of the epicenter. In addition, the ground motion data in the near field are also used from IRIS (Incorporated Research Institutions The equations of carrier phase (L) and code observations (pseudorange P) of dual-frequency GPS are expressed as [Jin et al, 2008[Jin et al, , 2016…”

Section: Observations and Methodsmentioning

confidence: 99%

“…The equations of carrier phase ( L ) and code observations (pseudorange P ) of dual‐frequency GPS are expressed as [ Jin et al ., , ]

\begin{matrix} left \\ L_{k, j}^{i} = λ_{k} ϕ_{k, j}^{i} = ρ_{0, j}^{i} - d_{ion, k, j}^{i} + d_{trop, j}^{i} + c (τ^{i} - τ_{j}) - λ_{k} (b_{k, j}^{i} + N_{k, j}^{i}) \\ P_{k, j}^{i} = ρ_{0, j}^{i} + d_{ion, k, j}^{i} + d_{trop, j}^{i} + c (τ^{i} - τ_{j}) + d_{q, k}^{i} + d_{q, k, j} + ε_{j}^{i} \end{matrix}

where subscript k stands for the frequency ( k = 1, 2), superscripts i and j represent the satellite and ground‐based GPS receiver, respectively, ρ 0 is the true distance between the GPS receiver and satellite, d ion and d trop are the ionospheric and tropospheric delays, c is the speed of light in vacuum space, τ is the satellite or receiver clock offset, b is the phase delay of satellite and receiver instrument bias, dq is the code delay of satellite and receiver instrument bias, λ is the carrier wavelength, φ is the total carrier phase between the satellite and receiver, N is the ambiguity of the carrier phase, and ε is other residuals. Ignoring the high‐order ionospheric effect in the Appleton‐Hartree equation, the ionospheric total electron content (TEC) along the signal path could be derived from the dual‐frequency GPS carrier phase and pseudorange measurements as [ Jin et al ., , ]

\begin{matrix} T E C = \frac{{f_{1}}^{2} {f_{2}}^{2}}{40.28 ({f_{1}}^{2} - {f_{2}}^{2})} (L_{1} - L_{2} + λ_{1} (N_{1} +)) \end{matrix}

…”

Section: Introductionmentioning

confidence: 99%

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GPS detection of ionospheric Rayleigh wave and its source following the 2012 Haida Gwaii earthquake

Jin

2017

JGR Space Physics

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The processes and sources of seismo‐ionospheric disturbances are still not clear. In this paper, coseismic ionospheric disturbances (CIDs) are investigated by dual‐frequency GPS observations following the Mw = 7.8 earthquake as results of the oblique‐thrust fault in the Haida Gwaii region, Canada, on 28 October 2012. Results show that the CIDs with an amplitude of up to 0.15 total electron content units (TECU) are found with spreading out at 2.20 km/s, which agree well with the Rayleigh wave propagation speed at 2.22 km/s detected by the bottom pressure records at about 10 min after the onset. The CIDs are a result of the upward propagation acoustic waves trigged by the Rayleigh wave in sequence from near field to far field. The strong correlation is found between the CIDs and the vertical ground motion recorded by seismometers nearby the epicenter. The total electron content (TEC) series from lower‐elevation angle GPS observations have higher perturbation amplitudes. Furthermore, the simulated ionospheric disturbance following a vertical Gauss pulse on the ground based on the finite difference time domain method confirms the ionospheric Rayleigh wave signature in the near field and the vertical ground motion dependence theoretically. The vertical ground motion is the dominant source of the ionospheric Rayleigh wave and affects the CID waveform directly.

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Section: Observations and Methodsmentioning

confidence: 99%

“…The equations of carrier phase ( L ) and code observations (pseudorange P ) of dual‐frequency GPS are expressed as [ Jin et al ., , ]

\begin{matrix} left \\ L_{k, j}^{i} = λ_{k} ϕ_{k, j}^{i} = ρ_{0, j}^{i} - d_{ion, k, j}^{i} + d_{trop, j}^{i} + c (τ^{i} - τ_{j}) - λ_{k} (b_{k, j}^{i} + N_{k, j}^{i}) \\ P_{k, j}^{i} = ρ_{0, j}^{i} + d_{ion, k, j}^{i} + d_{trop, j}^{i} + c (τ^{i} - τ_{j}) + d_{q, k}^{i} + d_{q, k, j} + ε_{j}^{i} \end{matrix}

\begin{matrix} T E C = \frac{{f_{1}}^{2} {f_{2}}^{2}}{40.28 ({f_{1}}^{2} - {f_{2}}^{2})} (L_{1} - L_{2} + λ_{1} (N_{1} +)) \end{matrix}

…”

Section: Introductionmentioning

confidence: 99%

GPS detection of ionospheric Rayleigh wave and its source following the 2012 Haida Gwaii earthquake

Jin

2017

JGR Space Physics

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“…Unlike the GPS whose constellation consists only of Medium Earth Orbit (MEO) satellites, the BDS constellation is comprised of MEO, Geostationary Orbit (GEO) as well as Inclined Geosynchronous Orbit (IGSO) satellites (Montenbruck et al 2013). Nowadays, the use of the BDS to study the ionosphere is continuously expanding (Jin et al 2016;Li et al 2012;Tang et al 2014;Xue et al 2015;. …”

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confidence: 99%

On the short-term temporal variations of GNSS receiver differential phase biases

Zhang

Teunissen

Yuan

2016

J Geod

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Abstract. As a first step towards studying the ionosphere with the Global Navigation Satellite System (GNSS), leveling the phase to the code geometry-free observations on an arc-by-arc basis yields the ionospheric observables, interpreted as a combination of slant total electron content along with satellite and receiver Differential Code Biases (DCB). The leveling errors in the ionospheric observables may arise during this procedure, which, according to previous studies by other researchers, are due to the combined effects of the code multipath and the intra-day variability in the receiver DCB. In this paper we further identify the short-term temporal variations of receiver Differential Phase Biases (DPB) as another possible cause of leveling errors. Our investigation starts by the development of a method to epoch-wise estimate Between-Receiver DPB (BR-DPB) employing (inter-receiver) single-differenced, phase-only 2GNSS observations collected from a pair of receivers creating a zero or short baseline. The key issue for this method is to get rid of the possible discontinuities in the epoch-wise BR-DPB estimates, occurring when satellite assigned as pivot changes. Our numerical tests, carried out using GPS (Global Positioning System, US GNSS) and BDS (BeiDou Navigation Satellite System, Chinese GNSS) observations sampled every 30 seconds by a dedicatedly selected set of zero and short baselines, suggest two major findings. First, epoch-wise BR-DPB estimates can exhibit remarkable variability over a rather short period of time (e.g. 6 centimeters over 3 hours), thus significant from a statistical point of view. Second, a dominant factor driving this variability is the changes of ambient temperature, instead of the un-modelled phase multipath.

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“…Due to eliminating some common errors in the system, the differential positioning technology has been commonly used in positioning tasks and applications with higher accuracy requirements [6][7][8]. With this technology, all the differential data of base stations are sent to the data center and then return to mobile station after calculation.…”

Section: Introductionmentioning

confidence: 99%

Fog Computing‐Based Differential Positioning Method for BDS

Wang

2018

Wireless Communications and Mobile Computing

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As one of the four global satellite navigation and positioning systems, BeiDou satellite navigation system (BDS) has received increasingly more attention. The differential positioning technology of BDS has greatly enhanced its accuracy and meets the needs of high-precision applications, but its positioning time still has much room for improvement. Fog computing allows the use of its services with low latency and mobility support to make up for the disadvantages of differential positioning algorithm. The paper proposes the fog computing-based differential positioning (FCDP) method which introduces fog computing technology to BDS. Compared with the original data center-based differential positioning (DCDP) method, the simulation results demonstrate that the FCDP method decreases the latency of positioning, while assuring the positioning accuracy.

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Assessment of BeiDou differential code bias variations from multi-GNSS network observations

Cited by 79 publications

References 34 publications

GPS detection of ionospheric Rayleigh wave and its source following the 2012 Haida Gwaii earthquake

GPS detection of ionospheric Rayleigh wave and its source following the 2012 Haida Gwaii earthquake

On the short-term temporal variations of GNSS receiver differential phase biases

Fog Computing‐Based Differential Positioning Method for BDS

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