Ariel is the M4 mission of the ESA’s Cosmic Vision Program 2015-2025, whose aim is to characterize by lowresolution transit spectroscopy the atmospheres of over one thousand warm and hot exoplanets orbiting nearby stars. It has been selected by ESA in March 2018 and adopted in November 2020 to be flown, then, in 2029. It is the first survey mission dedicated to measuring the chemical composition and thermal structures of the atmospheres of hundreds of transiting exoplanets, in order to enable planetary science far beyond the boundaries of the Solar System. The Payload (P/L) is based on a cold section (PLM – Payload Module) working at cryogenic temperatures and a warm section, located within the Spacecraft (S/C) Service Vehicle Module (SVM) and hosting five warm units operated at ambient temperature (253-313 K). The P/L and its electrical, electronic and data handling architecture has been designed and optimized to perform transit spectroscopy from space during primary and secondary planetary eclipses in order to achieve a large set of unbiased observations to shed light and fully understand the nature of exoplanets atmospheres, retrieving information about planets interior and determining the key factors affecting the formation and evolution of planetary systems.
The polarimetric and helioseismic imager instrument for the Solar Orbiter mission from the European Space Agency requires a high stability while capturing images, specially for the polarimetric ones. For this reason, an image stabilization system has been included in the instrument. It uses global motion estimation techniques to estimate the jitter in real time with subpixel resolution. Due to instrument requirements, the algorithm has to be implemented in a Xilinx Virtex-4QV field programmable gate array. The algorithm includes a 2-D paraboloid interpolation algorithm based on 2-D bisection. We describe the algorithm implementation and the tests that have been made to verify its performance. The jitter estimation has a mean error of 125 pixel of the correlation tracking camera. The paraboloid interpolation algorithm provides also better results in terms of resources and time required for the calculation (at least a 20% improvement in both cases) than those based on direct calculation.
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