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.
ARIEL (Atmospheric Remote-sensing InfraRed Large-survey) is the fourth medium-class mission (M4) of the European Space Agency, part of the Cosmic Vision program, whose launch is planned by late 2029. ARIEL aims to study the composition of exoplanet atmospheres, their formation and evolution. The ARIEL’s target will be a sample of about 1000 planets observed with one or more of the following methods: transit, eclipse and phase-curve spectroscopy, in both visible and infrared light. The scientific payload is composed by a reflective telescope having a 1m-class elliptical primary mirror, built in solid Aluminum, and two focal-plane instruments: FGS and AIRS. FGS (Fine Guidance System)3 has the double purpose of performing photometry (0.50-0.55 µm) and low resolution spectrometry over three bands (from 0.8 to 1.95 µm) and, simultaneously, to provide data to the spacecraft AOCS (Attitude and Orbit Control System). AIRS (ARIEL InfraRed Spectrometer) instrument will perform IR spectrometry in two wavelength ranges: between 1.95 and 3.9 µm (with a spectral resolution R > 100) and between 3.9 and 7.8 µm with a spectral resolution R > 30. This paper provides the status of the ICU (Instrument Control Unit), an electronic box whose purpose is to command and supply power to the AIRS warm front-end (as well as acquire science data from its two channels) and to command and control the TCU (Telescope Control Unit).
PLATO (PLAnetary Transits and Oscillations of stars) is the ESA’s third medium-class mission (M3), adopted in 2017 under the Cosmic Vision 2015-2025 program after selection in 2014. Set for launch in 2026 from French Guiana’s Kourou, its primary goal is to discover and provide an initial bulk characterization of diverse exoplanets, including rocky ones, orbiting bright solar-type stars. Operating from a halo orbit around L2, 1.5 million km from Earth, PLATO’s Payload consists of 26 telescopes (24 normal, 2 fast) capturing images every 25 seconds and 2.5 seconds, respectively. These work in tandem with the AOCS (S/C Attitude and Orbit Control System). Each camera comprises four CCDs, yielding 20.3 MP images—81.4 MP per normal camera and 2.11 gigapixels overall. The onboard P/L Data Processing System (DPS) handles this huge data volume, employing Normal and Fast DPUs along with a single ICU. The ICU manages data compression, overseeing the P/L through a SpaceWire network. This paper provides a comprehensive overview of the Instrument Control Unit’s (ICU) status following the rigorous performance test conducted on the Engineering Model (EM) and its evolution during the development phases of the Engineering Qualification Model (EQM) and Proto-Flight Model (PFM). The content delineates the outcomes derived from the extensive performance test executed on the Engineering Model (EM), detailing the meticulous activities undertaken during the Assembly, Integration, and Verification (AIT/AIV) processes of the EQM. Additionally, it explains the status of the Proto-Flight Model (PFM), offering insights into its development path.
KEYWORDS: Data processing, Technetium, Diagnostics, Control systems, Automation, Data communications, Thulium, Telecommunications, Design, Virtual reality
This paper presents a methodology to automate and accelerate the PLATO Payload (P/L) Boot Software (BSW) testing procedures by presenting a set of pre-programmed TCL scripts with different verification targets, satisfying the BSW requirements. These scripts are conceived in order to run an autonomous regression testing while verifying the BSW core functionalities, and in case of an additional BSW verification is needed, a set of scripts will be available for obtaining an automatic quick health-statement. The present method was proven by carrying out the pre-programmed functional and performance tests on the different PLATO’s BSW versions installed on the ICU development models. The tests performed on these models have proven their effectiveness during the BSW testing process, since the testing time has been greatly reduced and the test results can be archived to maintain a useful record that contemporaneously with the dedicated TCL scripts may assist in future verification of the flight BSW version.
The PLAnetary Transits and Oscillations of stars (PLATO) is a space telescope under ESA development. The (PLATO’s) Instrument Control Unit (ICU) is an electronics box that is responsible for the management (MGT) of the payload (P/L), the communication with the Service Module (SVM), and the compression of scientific data before transmitting them as telemetries TMs to the SVM. The ICU receives data from 2 “fast” (F-DPU) each 2.5s and 24 normal Data Processing Units (N-DPU) each 25s. In order to reduce the huge data volume produced on-board by the 104 CCD (4 CCD per camera), for each target star it will be allocated a window, from which all the pixel values will be gathered, forming a small image called “imagette”. These cropped images are compressed by means of a lossless algorithm running in the ICU FPGA and transmitted as Packet Utilization Standard (PUS) packets to SVM. These streamlined transmissions require qualified compression and decompression techniques to preserve images. In this poster we propose a scripting tool that classifies and collects automatically telemetry PUS packets, hosting scientific data and metadata, to reconstruct compressed imagettes on-ground.
PLAnetary Transits and Oscillations of stars (PLATO) is a mission belonging to the European Space Agency Cosmic Vision program which objective is to find and study extrasolar planetary systems. PLATO is composed of 26 telescopes which will observe uninterruptedly Sun like stars in order to identify a periodic decrease of the star brightness indicating the possible transit of an exoplanet. The PLATO on-board Data Processing System (DPS) consists of an Instrument Control Unit (ICU) and several distributed Digital Processing Units (DPUs) connected together by a SpaceWire network. The ICU collects and compresses scientific data from the DPUs and it implements the main data interface towards the satellite for telemetry and telecommands. The focus of this paper is on the Boot Software (BSW) of the ICU. The BSW is executed on a LEON3FT processor to perform system initialization, hardware checks, telecommand/telemetry management and the start of the ICU Application Software (ASW) responsible of the PLATO sub-system management necessary for the mission objectives. ICU BSW is the only boot software on-board PLATO and its high criticality level requires stringent verification/validation activities and a high-quality control of the software product which is achieved through extensive quality plans, multi-level testing and static analysis of software code. This paper describes the BSW dependable architecture along with the methods used to achieve the required performances, including FDIR techniques. Two engineering models of the ICU are going to be developed and the foreseen functional and performance tests will be presented in this paper.
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