Mass density of the upper atmosphere derived from Starlette’s Precise Orbit Determination with Satellite Laser Ranging

Jeon, Hyeonjin; Cho, S.; Kwak, Young‐Sil; Chung, Jong‐Kyun; Park, J. U.; Lee, D. K.; Kuzmicz-Cieslak, M.

doi:10.1007/s10509-010-0528-2

Cited by 9 publications

(7 citation statements)

References 24 publications

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“…The principle of the LLR observations is well documented (Murphy 2013;Murphy et al 2012). Besides the lunar applications, the laser ranging technique is still intensively used for tracking Earth orbiting satellites, especially for very accurate orbital (Peron 2013;Lucchesi et al 2015) and geophysical studies (Matsuo et al 2013;Jeon et al 2011).…”

Section: Lunar Laser Rangingmentioning

confidence: 99%

The new lunar ephemeris INPOP17a and its application to fundamental physics

Viswanathan

Fienga

Minazzoli

et al. 2018

Monthly Notices of the Royal Astronomical Society

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We present here the new INPOP lunar ephemeris, INPOP17a. This ephemeris is obtained through the numerical integration of the equations of motion and of rotation of the Moon, fitted over 48 years of Lunar Laser Ranging (LLR) data. We also include the 2 years of infrared (IR) LLR data acquired at the Grasse station between 2015 and 2017. Tests of the universality of free fall are performed. We find no violation of the principle of equivalence at the 10 −14 level. A new interpretation in the frame of dilaton theories is also proposed.

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Section: Lunar Laser Rangingmentioning

confidence: 99%

The new lunar ephemeris INPOP17a and its application to fundamental physics

Viswanathan

Fienga

Minazzoli

et al. 2018

Monthly Notices of the Royal Astronomical Society

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“…The estimation of the atmospheric drag coefficient could be found with various intervals. The frequency of the estimation of the atmospheric drag coefficient affected the accuracy of the orbit estimation results [ 8 , 9 , 34 , 35 ]. The atmospheric drag coefficient was estimated at intervals of 1, 2, 8, 12, and 24 h in the research.…”

Section: Short-arc Orbit Estimation With the Optical Observation Dmentioning

confidence: 99%

Optical Tracking Data Validation and Orbit Estimation for Sparse Observations of Satellites by the OWL-Net

Choi

Yim

et al. 2018

Sensors

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An Optical Wide-field patroL-Network (OWL-Net) has been developed for maintaining Korean low Earth orbit (LEO) satellites’ orbital ephemeris. The OWL-Net consists of five optical tracking stations. Brightness signals of reflected sunlight of the targets were detected by a charged coupled device (CCD). A chopper system was adopted for fast astrometric data sampling, maximum 50 Hz, within a short observation time. The astrometric accuracy of the optical observation data was validated with precise orbital ephemeris such as Consolidated Prediction File (CPF) data and precise orbit determination result with onboard Global Positioning System (GPS) data from the target satellite. In the optical observation simulation of the OWL-Net for 2017, an average observation span for a single arc of 11 LEO observation targets was about 5 min, while an average optical observation separation time was 5 h. We estimated the position and velocity with an atmospheric drag coefficient of LEO observation targets using a sequential-batch orbit estimation technique after multi-arc batch orbit estimation. Post-fit residuals for the multi-arc batch orbit estimation and sequential-batch orbit estimation were analyzed for the optical measurements and reference orbit (CPF and GPS data). The post-fit residuals with reference show few tens-of-meters errors for in-track direction for multi-arc batch and sequential-batch orbit estimation results.

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“…5 and 6, we determined the uncertainties in the conductivity and the EEF associated with the empirical model outputs in order to precisely determine the confidence limit in their magnitude. Although a large number of works deal with the comparisons between neutral atmosphere data and MSIS model prediction (Richards 2002;Liu et al 2005;Burke et al 2007;Park et al 2008;Jeon et al 2011), observed ionospheric data and IRI model predictions Batista et al 1996;de Souza et al 2003;Sethi et al 2004;Bertoni et al 2006;Lühr and Xiong 2010;Kenpankho et al 2011;Oyekola and Fagundes 2012;Yue et al 2013;Kumar et al 2014Kumar et al , 2015, and geomagnetic field data and IGRF predictions (Lowes 2000;Lowes and Olsen 2004), uncertainties (or potential errors) of these empirical models have not been published, even in Bilitza and Reinisch (2008), Picone et al (2002), and Finlay et al (2010).…”

Section: Analysis Of Linear Fittingmentioning

confidence: 99%

Influence of uncertainties of the empirical models for inferring the E-region electric fields at the dip equator

et al. 2016

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Daytime E-region electric fields play a crucial role in the ionospheric dynamics at the geomagnetic dip latitudes. Due to their importance, there is an interest in accurately measuring and modeling the electric fields for both climatological and near real-time studies. In this work, we present the daytime vertical (Ez) and eastward (Ey) electric fields for a reference quiet day (February 7, 2001) at the São Luís Space Observatory, Brazil (SLZ, 2.31°S, 44.16°W). The component Ez is inferred from Doppler shifts of type II echoes (gradient drift instability) and the anisotropic factor, which is computed from ion and electron gyro frequencies as well as ion and electron collision frequencies with neutral molecules. The component Ey depends on the ratio of Hall and Pedersen conductivities and Ez. A magnetic field-line-integrated conductivity model is used to obtain the anisotropic factor for calculating Ez and the ionospheric conductivities for calculating Ey. This model uses the NRLMSISE-00, IRI-2007, and IGRF-11 empirical models as input parameters for neutral atmosphere, ionosphere, and geomagnetic field, respectively. Consequently, it is worth determining the uncertainties (or errors) in Ey and Ez associated with these empirical model outputs in order to precisely define the confidence limit for the estimated electric field components. For this purpose, errors of ±10 % were artificially introduced in the magnitude of each empirical model output before estimating Ey and Ez. The corresponding uncertainties in the ionospheric conductivity and electric field are evaluated considering the individual and cumulative contribution of the artificial errors. The results show that the neutral densities and temperature may be responsible for the largest changes in Ey and Ez, followed by changes in the geomagnetic field intensity and electron and ions compositions.

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Mass density of the upper atmosphere derived from Starlette’s Precise Orbit Determination with Satellite Laser Ranging

Cited by 9 publications

References 24 publications

The new lunar ephemeris INPOP17a and its application to fundamental physics

The new lunar ephemeris INPOP17a and its application to fundamental physics

Optical Tracking Data Validation and Orbit Estimation for Sparse Observations of Satellites by the OWL-Net

Influence of uncertainties of the empirical models for inferring the E-region electric fields at the dip equator

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