NELIOTA is a new ESA activity launched at the National Observatory of Athens in February 2015 aiming to determine the distribution and frequency of small near-earth objects via lunar monitoring. The objective of this 3.5 year activity is to design, develop and implement a highly automated lunar monitoring system, which will conduct an observing campaign for 2 years, starting in the Summer 2016, in search of NEO impact flashes on the Moon. The project involves: (i) a complete refurbishment of the 40 year old 1.2m Kryoneri telescope of the National Observatory of Athens, (ii) development of a Lunar imager for the prime focus with two fast-frame sCMOS cameras, and (iii) procurement of servers for data processing and storage. Furthermore, we have developed a software system that controls the telescope and the cameras, processes the images and automatically detects lunar flashes. NELIOTA provides a web-based user interface, where the impact events, after their verification and characterization, will be reported and made available to the scientific community and the general public. The novelty of this project is the dedication of a large, 1.2m telescope for lunar monitoring, which is expected to characterize the frequency and distribution of NEOs weighing as little as a few grams.
KEYWORDS: Software development, Standards development, Space operations, Document management, Software engineering, Astronomy, System on a chip, Seaborgium, Robotics, Space robots
Science projects which require a large software development may use many scientists alongside a few professional
software engineers. Such projects tend to show extreme cases of the general problems associated with software
developments.
After introducing an example of a large software development in a science project, the importance of a development
management plan will be emphasised and sections of the plan highlighted and it is explained how these sections address
and prepare for the expected problems throughout the life of the project.
A positive, strongly proactive quality assurance, QA, approach is the common theme throughout. The role of QA is,
therefore, more to guide, support and advise all members of the team rather than only to detect and react to problems.
The top five problem areas addressed are:
1. Vague, late and missing requirements.
2. Few professional software engineers in a large software development.
3. A lack of testers with an appropriate test mentality.
4. Quality Assurance people cannot be everywhere, nor have in-depth skills in every subject.
5. Scientists will want to start coding and see writing documents as a waste of their time.
KEYWORDS: Space operations, Telescopes, Space telescopes, Satellites, Data processing, Astronomy, Stars, Electroluminescent displays, Charge-coupled devices, System on a chip
With the successful launch of the next generation space astrometry mission Gaia* in December 2013, this paper is going to provide an overview and status of this mission after its first half year of operations in space. We will provide a summary of the performed commissioning activities, the obtained findings, and how these first months of working on real data is impacting the DPAC operational concepts. The results will also provide a first glimpse of what Gaia will deliver in its future catalog releases.
KEYWORDS: Space operations, Data processing, Copper, Calibration, Charge-coupled devices, System on a chip, Software development, Astronomy, Electroluminescent displays, Photometry
Gaia* is Europe's astrometry satellite which is currently entering its operational phase. The Gaia mission will determine the astrometric, photometric properties, as well as the radial velocities of over one billion stellar objects. The observations collected over 24 hours by Gaia will consist of several tens of, up to more than one hundred, million of imagery data files, and low and high resolution spectra. This avalanche of data will be handled by the Gaia Data Processing and Analysis Consortium (DPAC) which is tasked with the processing of the collected data and to ultimately compile the Gaia catalogue. In order to prepare itself for taking up this challenge, DPAC has conducted a number of campaigns simulating its daily operations. Here we will describe these operation rehearsals, their preparation, conduct, and the return of experience. The positive experiences from these campaigns are now being used to also conduct such campaigns for DPAC's long term processing, based on real data.
KEYWORDS: Seaborgium, Document management, Space operations, Interfaces, Standards development, Data archive systems, System on a chip, Data modeling, Robotics, Astronomy
The competences of the Science Ground Segment, for an ESA science mission, include: science operations planning,
science instrument handling, data reception and processing, and archiving as well as providing science support. This
paper presents a generic documentation structure applicable during the analysis, definition, implementation and
operational phases of an ESA Science Ground Segment.
This is the conclusion of the analysis performed in the scope of the current ESAC Science Ground Segment
developments and is derived from the experience of previous ESA science missions and the ESA standardization efforts
(ECSS Standards). It provides a guideline to support the Science Ground Segment documentation processes during all
mission phases; representing a new approach for the development of future ESA science missions, and providing an
initial documentation structure that might be tailored depending on the specific scientific, engineering and managerial
characteristics of each mission. This paper also describes the process followed to produce the generic documentation tree
and how the development and operations experience feedback in the updated versions of this generic documentation tree.
KEYWORDS: Software development, Copper, Space operations, Standards development, Seaborgium, Data processing, System on a chip, Software engineering, Distance measurement, Stars
The ESA satellite Gaia aims to measure the main astrometric parameters and generate an astrometric catalogue
of 109 objects with an accuracy on the micro-arcsec level. To reach this goal the European scientific community
has formed the Gaia Data Processing and Analysis Consortium (DPAC). DPAC includes the Science Operation
Centre (SOC) at ESAC and together they constitute the Gaia science ground segment, including a total of more
than 400 scientists and engineers. Such a large group of developers represent a massive development effort which
requires effective quality monitoring and assurance mechanisms and reporting structures to be in place. In this
paper we will outline the procedures and mechanisms setup within the consortium to assure that DPAC software
products and the necessary hardware will be ready when they are needed and fulfill their expectations. The
experiences gathered in the employed PA/QA process, which is based on the relevant ECSS standards, will be
described and will prove useful for other projects of similarly large scale.
The Gaia Data Processing and Analysis Consortium (DPAC) is developing the required software to handle and
process the data collected during ESA’s Gaia astronomy mission. DPAC consist of more than 400 scientists
and engineers developing several dozens of large software packages. Such a large software development project
requires adequate progress monitoring techniques. DPAC has developed IMT as a semi automated monitoring
tool. In this paper we will describe the IMT system, the results it provides, and the experiences in view of usage
withing the DPAC management process. Also the potential usage of IMT in other large scientific projects is
discussed.
KEYWORDS: Data processing, Algorithm development, Software development, Systems modeling, Systems engineering, Astronomy, Current controlled current source, Satellites, Copper
Gaia is Europe's future astrometry satellite which is currently under development. The data collected
by Gaia will be treated and analyzed by the "Data Processing and Analysis Consortium" (DPAC). DPAC consists of over 400 scientists in more
than 22 countries, which are currently developing the required data reduction, analysis and handling algorithms and routines. DPAC is organized
in Coordination Units (CU's) and Data Processing Centres (DPCs). Each of these entities is individually responsible for the development of
software for the processing of the different data. In 2008, the DPAC Project Office (PO) has been set-up with the task to manage the day-to-day activities of the consortium including implementation, development and operations. This paper describes the tasks DPAC faces and the role of the DPAC PO
in the Gaia framework and how it supports the DPAC entities in their effort to fulfill the Gaia promise.
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