|Abstract:||Predicted GNSS satellite orbits and clocks, the so-called GNSS prediction products, have a key role in enhancing the convergence time of GNSS devices able to store the aforementioned products. Precise Point Positioning (PPP) techniques can also benefit from the use of this type of products, which can be used to improve the continuity of the solution in hazardous environments, where the updating rate of the GNSS products can considerably decrease. These predicted satellite orbits and clocks are the result of propagating restituted orbits and estimated clock models so that the quality of the prediction products do depend on the accuracy of the mentioned estimation process. The deployment of the Galileo constellation, with an increasing number of satellites along with the high stability of their in-orbit satellite clocks, brings a series of advantages to the GNSS community and, at the same time, raises a new set of challenges regarding the precise estimation of Galileo orbits and clocks. The estimation performance is driven, apart from the quality of the input GNSS observations, by the accuracy of the force models used to define the physical interaction of the GNSS satellites with their surrounding environment. The distance at which most of the GNSS constellations are deployed makes the solar radiation pressure the main non-gravitational perturbation effect. Given the relevance of the solar radiation effect, the GNSS community has dedicated a great effort to its analysis and modeling over the last decade, in particular for the GPS and GLONASS constellations. However, making the most out of the emerging Galileo constellation requires reviewing and adapting the current solar radiation models to the particular thermal, geometrical and optical properties of the Galileo IOV (In Orbit Validation) and FOC (Full Operational Constellation) satellites. Historically, a wide range of approaches to compensate for the solar radiation effect have been analyzed. These approaches can be classified into purely empirical, semi-empirical and analytical. On the one hand, empirical models are derived from collected observations, without relying on a-priori knowledge about the spacecraft, which makes their accuracy to be driven by the amount of collected observations and may lead to systematic errors. On the other hand, analytical models are based on the usage of the structural information of the satellite, provided by the manufacturers. These models are commonly affected by inaccuracies when extrapolating the in-orbit optical and thermal properties from the pre-launch values. Moreover, perturbations such as surface aging and disturbances in the attitude law mean an extra error source. An intermediate approach which exploits the advantages of the empirical and the analytical models is the box-wing model. In this case, the satellite is modelled as a box, representing the satellite bus, and two wings representing the solar panels. A priori values of the satellite properties are needed in order to fit the tracking data. With the exception of eclipse phases, GNSS satellites attitude law is given by the commonly known as yaw-steering (YS) mode. Within this mode the spacecraft performs a continuous rotation around the Earth-pointing axis, the so called “yaw” axis, with a twofold objective: ensuring the perpendicularity between the solar panels and the Sun radiation and keeping the navigation antenna pointing to the Earth’s center (except for IRNSS, as their satellites point to the Indian region). However, several publications have demonstrated the existence of misalignments of the solar panels orientation from the nominal attitude law, as well as non-symmetrical re-radiation effects, which lead to accelerations acting in the solar panel axis. This paper describes and tests a two-step solar radiation pressure (SRP) model. First, a box-wing model, refined for Galileo IOV and FOC satellites, provides the analytical accelerations due to the solar radiation pressure. Then, CODE’s new ECOM2 model is applied with the objective of reducing the error introduced by the non-modeled forces. Note that, the initial step provided by the box-wing model highly reduces the estimation efforts of the ECOM2 with a considerable enhance of the estimation accuracy. The approach described in the previous paragraph has been developed and tested as an upgrade of the state-of-the-art level GNSS tool property of GMV, magicGNSS. The proposed box-wing model fits the tracking data analyzed over a year period of the Galileo constellation. The SRP model has been validated by analyzing its impact on the laser ranging residuals over the considered period of time, by assessing the consistency of overlapped estimations and by evaluating the impact on the long term prediction error. The results will be compared with those obtained by using a single-step estimation based on the ECOM-2. In this way, the advantages of considering the a priori knowledge of the satellite’s properties will be highlighted.|
Proceedings of the 29th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2016)
September 12 - 16, 2016
Oregon Convention Center
|Pages:||2849 - 2863|
|Cite this article:||
García, A., Luque, D., Navarro, P.F., Tobías, G., "Galileo Simple Box-wing Model Plus ECOM for Improving Orbit and Clock Prediction Performances," Proceedings of the 29th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2016), Portland, Oregon, September 2016, pp. 2849-2863.
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