The Meteosat Third Generation (MTG) Programme is a EUMETSAT geostationary satellite mission developed by the European Space Agency (ESA). It will ensure the future continuity with, and enhancement of, operational meteorological (and climate) data from Geostationary Orbit as currently provided by the Meteosat Second Generation (MSG) system. The MTG satellites series is composed of 4 MTG-I and 2 MTG-S to bring to the meteorological community a continuous Imagery and Sounding capabilities with high spatial, spectral, and temporal resolution observations including geophysical parameters of the Earth based on state-of-the-art sensors. The first satellite (MTG-I1) was launched on 13th December 2022 by an Ariane 5 rocket. The commissioning of the whole system is expected to span over 2023. As part of the space segment of the mission, ESA and EUMETSAT performed the commissioning phase with the support of the Prime Contractor and the main unit's sub-contractors and suppliers. The recurrent satellites are being integrated and stored awaiting the availability of launchers, with a plan to launch MTG-S1 in Q1/2025 and MTG-I2 in Q1/2026. The main elements of the MTG-S1 satellite are now integrated and undergoing module level on-ground testing. This paper will address the overall mission and its instruments high level design features. It will introduce the MTG-I1 satellite performances as measured in-orbit and processed during the commissioning phase, before entering the routine operations and will discuss the future.
In the frame of the future satellite mission Meteosat Third Generation (MTG) undertaken by ESA, Thales Alenia Space,
as satellite prime contractor, is responsible for the design, validation and monitoring of the geometric image quality.
All final products delivered by the MTG mission will be geolocated on-ground by the Image Navigation Registration
(INR) process. This process estimates the geolocation of every acquired sample thanks to a Kalman filter based on
observables extracted from the images (e.g landmarks, stars) as well as auxiliary data such as orbit, attitude or scan
mirror measurements.
The paper presents the high-fidelity engineering tool developed to assess and analyze the future INR performances of the
system. Compared to previous Meteosat generations based on spinning satellites, the 3-axis stabilisation increases the
complexity of the INR model prediction by inducing high-frequency perturbations.
In order to estimate the INR filter behaviour, realistic sets of image observables are simulated. The simulation takes into
account all error sources affecting the pointing knowledge of each MTG instrument such as micro-vibrations, thermoelastic deformations, orbit estimation errors or instrument scan and spacecraft attitude knowledge performances. After simulating the INR process over the images, geometric performances as defined through MTG user specifications are assessed. Thus, the INR behaviour and the overall system performance can be predicted among different operational conditions. It is then possible to analyse the contribution of each perturbation to the final performances and to tune the INR filter with respect to the satellite behaviour.
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