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 modeling, Image compression, Data processing, Data compression, Cameras, Satellites, Data acquisition, Algorithm development, Satellite communications, Performance modeling
PLAnetary Transits and Oscillations of stars (PLATO) is a medium-class mission selected by ESA in the framework of the Cosmic Vision programme. The PLATO Instrument Control Unit (ICU) is responsible for the management of the scientific payload, the communication with the satellite on board computer, the acquisition of housekeeping and scientific data from the 26 PLATO cameras and their processing before the downloading to the satellite mass memory unit. The data produced by the cameras cannot be transmitted directly to ground as soon as they are acquired but an onboard pre-processing and compression is needed. While the pre-processing stage is in charge of the camera's Data Processing Units (DPUs), the compression is executed on board ICU. Due to the highly demanding science requirements, the compression must be rigorously lossless. In this paper we will review the overall ICU onboard data processing chain, from the DPUs to the satellite mass memory, presenting the compression strategies implemented in the ICU application software architecture, and the results of the performance test run on the ICU Engineering Model.
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 PLATO mission, part of ESA’s Cosmic Vision program, is expected to be launched by 2026 and will focus on discovering exoplanets from gas giants down to small rocky planets. Equipped with telescopes and cameras, including 24 normal and 2 fast cameras, it mainly aims to find Earth-sized planets in the habitable zone of Sun-type stars. The Data Processing System, comprising DPUs and the ICU, manages payload operations, with an On-Board Control Procedures (OBCP) engine enhancing autonomy and flexibility. Written in OCL, OBCPs are independent procedures loaded into the ICU memory, enabling late-stage modifications and regular re-execution, reducing repetitive uploads and conserving bandwidth. In this paper, we present a brief overview of the OCL (On-Board Command) language and its features, as well as the capabilities and benefits of having OBCPs. We also describe the OBCP flight software environment and the OBCP engine implemented in the ASW, along with the features and capabilities of the OBCP for the PLATO mission.
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.
KEYWORDS: Operating systems, Spectroscopy, Data acquisition, Data processing, Telescopes, Infrared spectroscopy, Control systems, Computer architecture, Process control, Data communications
The ARIEL Instrument Control Unit (ICU) implements the monitoring, control, and commanding of both the ARIEL IR Spectrometer (AIRS) and Telescope Control Unit (TCU). It acquires the AIRS scientific data provided by the AIRS detector control units and implements the onboard pre-processing and downlink to the satellite Mass Memory. Based on a preliminary Technical Specification, a high-level preliminary software architecture has been produced. In this paper we provide the ARIEL ICU Application SW layers description and some examples of the static and dynamic diagrams that will be included in the final architecture
PLAnetary Transits and Oscillations of stars (PLATO) is a medium-class mission selected by ESA in the framework of the Cosmic Vision programme. The PLATO Instrument Control ICU is responsible for the management of the scientific payload, the communication with the SVM, and the lossless compression of scientific data before the download to the satellite Mass memory. The ICU requirements have been finalized for the Preliminary Design Review. The resulting technical specification has been used to design a Model Based Software architecture. The first two versions of the PLATO ICU SW have been released and fully validated on the target platform. This paper provides the details of the solutions adopted to cover all implemented services.
PLATO (PLAnetary Transits and Oscillations of stars) is the third medium-class mission (M3), selected by the European Space Agency (ESA) in 2014 and adopted in 2017 for the Cosmic Vision 2015-2025 scientific program. The launch is scheduled in 2026 from the French Guiana (Kourou) for a nominal in-orbit lifetime of 4 years plus up to 4 years of possible extension. The main purpose of the mission is the discovery and preliminary characterization of many different types of exoplanets down to rocky terrestrial planets orbiting around bright solar-type stars. The PLATO spacecraft will operate from a halo orbit around L2 (the Sun-Earth 2nd Lagrangian Point), a virtual point in space, 1.5 million km beyond Earth as seen from the Sun and its Payload will consist of 26 small telescopes (24 normal and 2 fast), pointing at the same target stars, that provide images every 25 seconds with the normal camera and every 2.5 seconds for the two fast cameras, operating in a close loop with the AOCS (S/C Attitude and Orbit Control System). Each camera (consisting of a telescope, the Focal Plane Assembly and its Front-End Electronics) will host four CCDs producing 20.3 megapixels images adding up to 81.4 megapixels per normal camera and 2.11 gigapixels for the overall Payload (P/L). This huge amount of data cannot be transmitted to the ground and need to be processed on-board by the P/L Data Processing System (DPS) made up of various processing electronic units. The DPS of the PLATO instrument comprises the Normal and Fast DPUs (Data Processing Units) and a single ICU (Instrument Control Unit), in charge of HW and SW lossless data compression and managing the P/L through a SpaceWire (SpW) network. In this paper we will review the status of the Instrument Control Unit (ICU) after its Critical Design Review (CDR) process, performed by ESA and PMC (PLATO Mission Consortium), the results of the performance test preliminary run on the Engineering Model (EM), waiting for the following Engineering and Qualification Model (EQM) and Proto-Flight Model (PFM), and the status of the early models development (Engineering Models 1 and 2, Mass and Thermal Dummy - MTD) that, along with the Boot SW (BSW) burning in PROM readiness, will enable the EQM manufacturing.
KEYWORDS: Process control, Data processing, Computer architecture, Control systems, Network architectures, Amplifiers, Operating systems, Space operations
In this paper we describe the activities towards the design of a common framework for the Instrument Control and Data Processing Units for the three scientific payload instruments on board the joint ESA-JAXA SPICA mission, currently at the end of its phase A study. In this context, we started a program to assess modular architectures based on the use of a quad-core fault-tolerant LEON4 SPARC V8 processor on a SpaceWire network. We will describe the results of our initial tests using both Asymmetric Multi processing (AMP) and Symmetric Multi Processing (SMP) configurations. In addition, the possibility to adopt the RTEMS real time operating system, already space qualified on single core processors, will be evaluated both in terms of latency performances and of dynamical allocation of the resources. Finally, we will present the outline of the way forward for the next phases of the SPICA project.
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