Computing GPS satellite velocity and acceleration from the broadcast navigation message

Navigation ◽  
2019 ◽  
Vol 66 (4) ◽  
pp. 769-779
Author(s):  
Blair F. Thompson ◽  
Steven W. Lewis ◽  
Steven A. Brown ◽  
Todd M. Scott
Keyword(s):  
Navigation Message ◽  
Satellite Velocity

Toward an Operational Navigation Message Authentication Service: Proposal and Justification of Additional OSNMA Protocol Features

2019 ◽  
Author(s):  
Ignacio Fernandez Hernandez ◽  
Tomer Ashur ◽  
Vincent Rijmen ◽  
Carlo Sarto ◽  
Simon Cancela ◽  
...  
Keyword(s):  
Message Authentication ◽  
Navigation Message

scholarly journals Can assembly bias explain the lensing amplitude of the BOSS CMASS sample in a Planck cosmology?

2020 ◽  
Vol 493 (4) ◽  
pp. 5551-5564
Author(s):  
Sihan Yuan ◽  
Daniel J Eisenstein ◽  
Alexie Leauthaud
Keyword(s):  
Cold Dark Matter ◽  
Cosmological Parameters ◽  
Bias Parameter ◽  
Projected Clustering ◽  
The Galaxy ◽  
Satellite Velocity ◽  
Galaxy Sample ◽  
Best Fitting ◽  
Galaxy Assembly ◽  
Halo Occupation Distribution

ABSTRACT In this paper, we investigate whether galaxy assembly bias can reconcile the 20–40 ${{\ \rm per\ cent}}$ disagreement between the observed galaxy projected clustering signal and the galaxy–galaxy lensing signal in the Baryon Oscillation Spectroscopic Survey CMASS galaxy sample. We use the suite of abacuscosmos lambda cold dark matter simulations at Planck best-fitting cosmology and two flexible implementations of extended halo occupation distribution (HOD) models that incorporate galaxy assembly bias to build forward models and produce joint fits of the observed galaxy clustering signal and the galaxy–galaxy lensing signal. We find that our models using the standard HODs without any assembly bias generalizations continue to show a 20–40 ${{\ \rm per\ cent}}$ overprediction of the observed galaxy–galaxy lensing signal. We find that our implementations of galaxy assembly bias do not reconcile the two measurements at Planck best-fitting cosmology. In fact, despite incorporating galaxy assembly bias, the satellite distribution parameter, and the satellite velocity bias parameter into our extended HOD model, our fits still strongly suggest a $\sim \! 34{{\ \rm per\ cent}}$ discrepancy between the observed projected clustering and galaxy–galaxy lensing measurements. It remains to be seen whether a combination of other galaxy assembly bias models, alternative cosmological parameters, or baryonic effects can explain the amplitude difference between the two signals.

GPS Satellite State Vector Determination in ECI Coordinate System using the Civil Navigation Message

2013 ◽  
Vol 67 (1) ◽  
pp. 1-16
Author(s):  
Ghangho Kim ◽  
Sanghoon Jeon ◽  
Changdon Kee ◽  
Tae Soo No ◽  
Kiho Kwon ◽  
...  
Keyword(s):  
Closed Form ◽  
Reference Frame ◽  
Calculated Data ◽  
Terrestrial Reference Frame ◽  
Navigation Data ◽  
Numerical Result ◽  
Resolution System ◽  
Satellite Velocity ◽  
Celestial Reference Frame ◽  
Simple Rotation

A closed form of an algorithm to determine a Global Positioning System (GPS) satellite's position, velocity and acceleration is proposed, and an Earth Centred Earth Fixed (ECEF) to Earth Centred Inertial (ECI) transformation result using the Civil Navigation (CNAV) message is presented in this paper. To obtain the closed form of the GPS satellite velocity and acceleration determination algorithm using the CNAV, we analytically differentiated the IS-GPS-200F position determination function. The calculated data are transformed from the International Terrestrial Reference Frame (ITRF) to the Geocentric Celestial Reference Frame (GCRF) using an equinox-based transform algorithm that is defined in the IAU-2000 resolution system using the Earth Orientation Parameter (EOP) data. To verify the correctness of the proposed velocity and acceleration determination algorithm, the analytical results are compared to the numerical result. The equinox-based transformation result is compared to simple rotation about the z-axis, which does not use the EOP. The results show that by using the proposed algorithm and the equinox-based transformation together, the user can obtain more accurate navigation data in the ECI frame.

scholarly journals A Comparison Between Numerical Differentiation and Kalman Filtering for a Leo Satellite Velocity Determination

2013 ◽  
Vol 48 (3) ◽  
pp. 103-110 ◽  
Author(s):  
M.A. Sharifi ◽  
M.R. Seif ◽  
M.A. Hadi
Keyword(s):  
Kalman Filtering ◽  
Velocity Vector ◽  
Numerical Differentiation ◽  
Filter Method ◽  
Newton Interpolation ◽  
Satellite Velocity ◽  
Kalman Filter Method ◽  
Range Rate ◽  
Noise Amplification ◽  
Leo Satellite

Abstract The kinematic orbit is a time series of position vectors generally obtained from GPS observations. Velocity vector is required for satellite gravimetry application. It cannot directly be observed and should be numerically determined from position vectors. Numerical differentiation is usually employed for a satellite’s velocity, and acceleration determination. However, noise amplification is the single obstacle to the numerical differentiation. As an alternative, velocity vector is considered as a part of the state vector and is determined using the Kalman filter method. In this study, velocity vector is computed using the numerical differentiation (e.g., 9-point Newton interpolation scheme) and Kalman filtering for the GRACE twin satellites. The numerical results show that Kalman filtering yields more accurate results than numerical differentiation when they are compared with the intersatellite range-rate measurements.

Sign in / Sign up

Export Citation Format

Share Document