Numerical modeling of a Global Navigation Satellite System in a general relativistic framework - Archive ouverte HAL
Article Dans Une Revue Advances in Space Research Année : 2011

Numerical modeling of a Global Navigation Satellite System in a general relativistic framework

Résumé

In this article we model a Global Navigation Satellite System (GNSS) in a Schwarzschild space-time, as a first approximation of the relativistic geometry around the Earth. The closed time-like and scattering light-like geodesics are obtained analytically, describing respectively trajectories of satellites and electromagnetic signals. We implement an algorithm to calculate Schwarzschild coordinates of a GNSS user who receives proper times sent by four satellites, knowing their orbital parameters; the inverse procedure is implemented to check for consistency. The constellation of satellites therefore realizes a geocentric inertial reference system with no a priori realization of a terrestrial reference frame. We perform a simulation of position determination and show that the determination of the four coordinates with a 25-32 digit accuracy takes only around 60 ms. Effects of non-gravitational perturbations on positioning errors are assessed, and methods to reduce them are sketched. In particular, inter-links between satellites could greatly enhance stability and accuracy of the positioning system. Effects of gravitational perturbations are omitted in this paper in order to make a clearer comparison between the relativistic and non-relativistic scheme, but they will be included in subsequent work. We believe that the final algorithm will be a serious alternative to the usual post-Newtonian scheme.

Dates et versions

hal-03733391 , version 1 (21-07-2022)

Identifiants

Citer

Pacôme Delva, Uros Kostic, Andrej Cadez. Numerical modeling of a Global Navigation Satellite System in a general relativistic framework. Advances in Space Research, 2011, 47, pp.370-379. ⟨10.1016/j.asr.2010.07.007⟩. ⟨hal-03733391⟩
8 Consultations
0 Téléchargements

Altmetric

Partager

More