Precise orbit determination based on raw GPS measurements

Zehentner, Norbert; Mayer‐Gürr, Torsten

doi:10.1007/s00190-015-0872-7

Cited by 56 publications

(48 citation statements)

References 28 publications

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“…PPP has a few advantages over relative positioning techniques such as RTK: no restriction with inter-station distances, direct determination of position solution, simple data processing and global capability. As a result, PPP is widely applied to near real-time meteorology (Rocken et al 2005;Lu et al 2016), crustal deformation monitoring (Calais et al 2006), orbit determination of low (Zehentner and Mayer-Gürr 2015), earthquake and tsunami monitoring and early warning (Li et al 2013;Chen et al 2015), and other geoscience applications.…”

Section: Multi-gnss Precise Point Positioning (Ppp)mentioning

confidence: 99%

Multi-GNSS precise point positioning for precision agriculture

Guo

et al. 2018

Precision Agric

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The main objective of this research was to examine the feasibility of Multi-GNSS precise point positioning (PPP) in precision agriculture (PA) through a series of experiments with different working modes (i.e. stationary and moving) under different observation conditions (e.g. open sky, with buildings or with canopy). For the stationary test carried out in open space in the UK, the positioning accuracy achieved was 13.9 mm in one dimension by a PPP approach, and the repeatability of positioning results was improved from 19.0 to 6.0 mm by using Multi-GNSS with respect to GPS only. For the moving test carried out in similar location in the UK, almost the same performance was achieved by GPS-only and by Multi-GNSS PPP. However, for a moving experiment carried out in China with obstruction conditions, Multi-GNSS improved the accuracy of baseline length from 126.0 to 35.0 mm and the repeatability from 110.0 mm to 49.0 mm, The results suggested that the addition of the BeiDou, Galileo and GLONASS systems to the standard GPS-only processing improved the positioning repeatability, while a positioning accuracy was achieved at about 20 mm level in the horizontal direction with an improvement against the GPS-only PPP results. In space-constrained and harsh environments (e.g. farms surrounded with dense trees), the availability and reliability of precise positioning decreased dramatically for the GPS-only PPP results, but limited impacts were observed for Multi-GNSS PPP. In addition, compared to real time kinematic (RTK) GNSS, which is currently most commonly used for high precision PA applications, similar accuracy has been achieved by PPP. In contrast to RTK GNSS, PPP can provide high accuracy positioning with higher flexibility and potentially lower capital and running costs. Hence, PPP might be a great opportunity for agriculture to meet the high accuracy requirements of PA in the near future.

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Section: Multi-gnss Precise Point Positioning (Ppp)mentioning

confidence: 99%

Multi-GNSS precise point positioning for precision agriculture

Guo

et al. 2018

Precision Agric

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“…In this study, the computation of ERP and SRP accelerations is based on the satellite's position taken from precise kinematic orbits (Zehentner and Mayer-Gürr 2016), but any orbit could be used. Accelerations are modeled in an inertial reference frame, where transformation to the satellite reference frame (SRF) is performed using star camera data.…”

Section: Extended Unified Model For Srp and Erpmentioning

confidence: 99%

Extended forward and inverse modeling of radiation pressure accelerations for LEO satellites

Vielberg

Kusche

2020

J Geod

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For low Earth orbit (LEO) satellites, activities such as precise orbit determination, gravity field retrieval, and thermospheric density estimation from accelerometry require modeled accelerations due to radiation pressure. To overcome inconsistencies and better understand the propagation of modeling errors into estimates, we here suggest to extend the standard analytical LEO radiation pressure model with emphasis on removing systematic errors in time-dependent radiation data products for the Sun and the Earth. Our extended unified model of Earth radiation pressure accelerations is based on hourly CERES SYN1deg data of the Earth's outgoing radiation combined with angular distribution models. We apply this approach to the GRACE (Gravity Recovery and Climate Experiment) data. Validations with 1 year of calibrated accelerometer measurements suggest that the proposed model extension reduces RMS fits between 5 and 27%, depending on how measurements were calibrated. In contrast, we find little changes when implementing, e.g., thermal reradiation or anisotropic reflection at the satellite's surface. The refined model can be adopted to any satellite, but insufficient knowledge of geometry and in particular surface properties remains a limitation. In an inverse approach, we therefore parametrize various combinations of possible systematic errors to investigate estimability and understand correlations of remaining inconsistencies. Using GRACE-A accelerometry data, we solve for corrections of material coefficients and CERES fluxes separately over ocean and land. These results are encouraging and suggest that certain physical radiation pressure model parameters could indeed be determined from satellite accelerometry data.

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“…However, the results of reduced-dynamic POD are not completely in agreement with the results of kinematic POD. Zehentner & Mayer-Gürr (2016) reported an improvement in orbit accuracy when estimating an individual slant TEC parameter in the kinematic POD processing to model the ionospheric influence, including high-order ionosphere effects. The different performances of high-order ionospheric corrections may be attributed to the methods of LEO POD that have been used.…”

Section: Journal Of Geophysical Research: Space Physicsmentioning

confidence: 99%

The Influence of Geomagnetic Storm of 7‐8 September 2017 on the Swarm Precise Orbit Determination

Zhang

Xiong

et al. 2019

JGR Space Physics

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We analyze a recent geomagnetic storm event on 7‐8 September 2017 to investigate the impact of geomagnetic storm on the precise orbit determination (POD) of Swarm constellation. The storm time performance of POD is analyzed. The quality of Swarm orbits are severely degraded during the storm main phase on 8 September and the maximum precision degradation reached over 10 cm. The enhanced thermospheric mass density at Swarm altitude during the storm enlarges the atmosphere drag for low Earth orbit satellites, which makes main contributions to the storm time degradation of Swarm orbit. This negative effect of enhanced atmosphere drag on the orbit estimation is mostly suppressed by estimating a more frequent atmosphere drag parameter. The higher‐order ionospheric effects on the POD of Swarm are also analyzed. The vertical total electron content derived from the Swarm onboard Global Positioning System receiver presents a larger enhancement on the dayside at low latitude and midlatitude during the storm main phase. This leads to an increase in the high‐order ionospheric effects, especially in the second‐order terms. No evident precision improvement is observed after correcting the high‐order ionospheric effects. The results demonstrate that during this geomagnetic storm, the enhanced thermospheric neutral density serves as a stronger error source than the enhanced ionospheric plasma density for the low Earth orbit satellite orbit determination processing.

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Precise orbit determination based on raw GPS measurements

Cited by 56 publications

References 28 publications

Multi-GNSS precise point positioning for precision agriculture

Multi-GNSS precise point positioning for precision agriculture

Extended forward and inverse modeling of radiation pressure accelerations for LEO satellites

The Influence of Geomagnetic Storm of 7‐8 September 2017 on the Swarm Precise Orbit Determination

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