Projet MOPS : Système dédié à l'utilisation des signaux GNSS pour l'océanographie et la surveillance de la surface de la mer

International audienceCe papier présente la réalisation d'un système avancé de réception de signaux GNSS qui enregistre simultanément le signal direct issu d'un satellite et le signal réfléchi par la surface maritime. La réception des signaux est réalisée à l'aide de deux antennes localisées à une dizaine de mètres au dessus de la surface maritime. Cette plateforme expérimentale est constituée de plusieurs éléments : un module électronique radiofréquence RF en bande L1 (1575.42 GHz), deux convertisseurs de fréquence intermédiaire FI (70 MHz), deux modules d'acquisition et de numérisation de signaux analogiques (8 GS/s sur 10 bits et 420 MS/s sur 12 bits). Le système ainsi réalisé doit permettre d'observer les fluctuations rapides et lentes de la surface de mer à petite et grande échelle avec de bonnes précisions. La constitution de cette plateforme s'inscrit dans le cadre du projet MOPS [1] porté par l'ENSTA-Bretagne, Télécom Bretagne et l'IFREMER. Ce projet est soutenu par le GIS Europôle Mer

The Athena X-ray Integral Field Unit: a consolidated design for the system requirement review of the preliminary definition phase

The Athena X-ray Integral Unit (X-IFU) is the high resolution X-ray spectrometer, studied since 2015 for flying in the mid-30s on the Athena space X-ray Observatory, a versatile observatory designed to address the Hot and Energetic Universe science theme, selected in November 2013 by the Survey Science Committee. Based on a large format array of Transition Edge Sensors (TES), it aims to provide spatially resolved X-ray spectroscopy, with a spectral resolution of 2.5 eV (up to 7 keV) over an hexagonal field of view of 5 arc minutes (equivalent diameter). The X-IFU entered its System Requirement Review (SRR) in June 2022, at about the same time when ESA called for an overall X-IFU redesign (including the X-IFU cryostat and the cooling chain), due to an unanticipated cost overrun of Athena. In this paper, after illustrating the breakthrough capabilities of the X-IFU, we describe the instrument as presented at its SRR, browsing through all the subsystems and associated requirements. We then show the instrument budgets, with a particular emphasis on the anticipated budgets of some of its key performance parameters. Finally we briefly discuss on the ongoing key technology demonstration activities, the calibration and the activities foreseen in the X-IFU Instrument Science Center, and touch on communication and outreach activities, the consortium organisation, and finally on the life cycle assessment of X-IFU aiming at minimising the environmental footprint, associated with the development of the instrument. Thanks to the studies conducted so far on X-IFU, it is expected that along the design-to-cost exercise requested by ESA, the X-IFU will maintain flagship capabilities in spatially resolved high resolution X-ray spectroscopy, enabling most of the original X-IFU related scientific objectives of the Athena mission to be retained. (abridged).Comment: 48 pages, 29 figures, Accepted for publication in Experimental Astronomy with minor editin

The Athena X-ray Integral Field Unit: a consolidated design for the system requirement review of the preliminary definition phase

The Athena X-ray Integral Unit (X-IFU) is the high resolution X-ray spectrometer studied since 2015 for flying in the mid-30s on the Athena space X-ray Observatory. Athena is a versatile observatory designed to address the Hot and Energetic Universe science theme, as selected in November 2013 by the Survey Science Committee. Based on a large format array of Transition Edge Sensors (TES), X-IFU aims to provide spatially resolved X-ray spectroscopy, with a spectral resolution of 2.5 eV (up to 7 keV) over a hexagonal field of view of 5 arc minutes (equivalent diameter). The X-IFU entered its System Requirement Review (SRR) in June 2022, at about the same time when ESA called for an overall X-IFU redesign (including the X-IFU cryostat and the cooling chain), due to an unanticipated cost overrun of Athena. In this paper, after illustrating the breakthrough capabilities of the X-IFU, we describe the instrument as presented at its SRR (i.e. in the course of its preliminary definition phase, so-called B1), browsing through all the subsystems and associated requirements. We then show the instrument budgets, with a particular emphasis on the anticipated budgets of some of its key performance parameters, such as the instrument efficiency, spectral resolution, energy scale knowledge, count rate capability, non X-ray background and target of opportunity efficiency. Finally, we briefly discuss the ongoing key technology demonstration activities, the calibration and the activities foreseen in the X-IFU Instrument Science Center, touch on communication and outreach activities, the consortium organisation and the life cycle assessment of X-IFU aiming at minimising the environmental footprint, associated with the development of the instrument. Thanks to the studies conducted so far on X-IFU, it is expected that along the design-to-cost exercise requested by ESA, the X-IFU will maintain flagship capabilities in spatially resolved high resolution X-ray spectroscopy, enabling most of the original X-IFU related scientific objectives of the Athena mission to be retained. The X-IFU will be provided by an international consortium led by France, The Netherlands and Italy, with ESA member state contributions from Belgium, Czech Republic, Finland, Germany, Poland, Spain, Switzerland, with additional contributions from the United States and Japan.The French contribution to X-IFU is funded by CNES, CNRS and CEA. This work has been also supported by ASI (Italian Space Agency) through the Contract 2019-27-HH.0, and by the ESA (European Space Agency) Core Technology Program (CTP) Contract No. 4000114932/15/NL/BW and the AREMBES - ESA CTP No.4000116655/16/NL/BW. This publication is part of grant RTI2018-096686-B-C21 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”. This publication is part of grant RTI2018-096686-B-C21 and PID2020-115325GB-C31 funded by MCIN/AEI/10.13039/501100011033

Traitement d'images et fusion de données pour la détection d'objets enfouis en acoustique sous-marine

Detection and classification of buried objects is a particularly difficult problem: synthetic aperture sonar techniques used for seabed imagery provide data with very low signal to noise ratio, and then a large number of false alarms. The goal of this thesis is to make and develop algorithms allowing to reduce the number of false alarms, by keeping a good detection, and eventually to classify the detected objects, thanks to image processing and data fusion tools.For that, 1st, 2nd, 3rd, and 4th order statistical properties of these images are used in order to develop efficient detection algorithms. To improve the results, the data extracted by these means are combined by a fusion process using the theory of evidence. This allows to classify each pixel of the image into "object" or "not object" depending on wether it is supposed to belong to a sought object (underwater mine for example) or not. The result can then be used by an expert in order to help him in his decision.La détection et la classification d'objets enfouis est un problème particulièrement délicat : les techniques de sonar à antenne synthétiques utilisées pour imager le fond sous-marin fournissent des données possédant souvent un très faible rapport signal à bruit, d'où un nombre important de fausses alarmes. L'objectif de la thèse est de concevoir et développer des algorithmes permettant de réduire le nombre de fauses alarmes, tout en conservant une bonne détection, et éventuellement de classifier les objets détectés, grâce à des outils de traitement d'images et de fusion de données.Pour cela, on utilise les propriétés statistiques aux ordres 1, 2, 3 et 4 de ces images sonar qui vont nous permettre de développer des algorithmes de détection performants. Afin d'améliorer le résultat, les données ainsi extraites sont fusionnées dans un processus basé sur la théorie de l'évidence. Ceci permet de classifier chaque pixel de l'image en "objet" ou "non objet" selon qu'il est supposé appartenir à un objet recherché (mine sous-marine par exemple) ou pas. Le résultat pourra alors être utilisé par un expert afin de l'aider dans sa prise de décision

Utilisation des statistiques d'ordres supérieurs en contrôle qualité de détecteurs de rayons X

International audienceA quality control method for X-ray detector is proposed in this paper. The process is based on the statistical properties of the images obtained with this detector. Higher Order Statistics (HOS) tools, and more specifically the kurtosis (4th order statistical value), are used on these images in order to highlight the regions of interest likely to contain artifacts a human expert has to detect rapidly. The properties of these small structures being different from the background, HOS allow to extract the corresponding regions from the rest of the image. The results (size and amplitude of the highlighted regions) will help the expert to analyse the artifact

Détection en Imagerie SAS par Fusion de Données de Statistiques Locales

International audienceLa détection de mines sous-marines est aujourd'hui un problème stratégique important. Les images fournies par un Sonar à Antenne Synthétique (SAS) sont alors d'un grand intérêt pour la détection et la classification d'objets posés sur le fond ou enfouis dans le sol marin. Cet article présente une méthode de détection de ces objets sous-marins utilisant la fusion, basée sur la théorie de l'évidence et des ensembles flous, de données statistiques locales préalablement extraites de l'image sonar. Ces données sont issues des propriétés statistiques des images SAS aux ordres 1, 2, 3 et 4

Automated Segmentation of SAS Images using the Mean - Standard Deviation Representation

A segmentation method of synthetic aperture sonar (SAS) images is presented, in order to highlight some characteristics (number, position, shape, ...) of underwater mines echoes. This segmentation method is based on statistical characteristics of the sonar images, highlighted by the mean – standard deviation plane. It is automated by using an entropy criterion

Higher Order Statistics for the Detection of Underwater Mines in SAS Imagery

Synthetic Aperture Sonar (SAS) imagery is largely used in detection, location, and classification of underwater mines laying or buried in the sea bed. This paper proposes a detection method using Higher Order Statistics (HOS) on SAS images. The proposed method can be divided into two steps. Firstly, the HOS (Skewness and Kurtosis) are locally estimated using a square sliding computation window. In a second step, the results are focused by a matched filtering. This enables the precise location of the objects. This method is tested on real SAS data containing both underwater mines laying on the seabed and buried objects

La théorie des fonctions de croyance : une alternative aux probabilités pour la perception et la fusion de données.

La théorie des fonctions de croyance permet de modéliser et synthétiser la connaissance dont on dispose sur le système observé. Elle est particulièrement bien adaptée pour développer des systèmes d'assistance humaine. Elle permet de détecter et de quantifier le conflit entre les sources d'informations. Elle est basée sur un formalisme mathématique solide et facilite la conception de systèmes de fusion de données. Les principes de base sont exposés sur des exemples simples. Deux applications réelles sont présentées

Choice of Acoustics Signals Family in Multi-Users Environment

International audienceIn an underwater acoustical context, our application concerns a system immersed, with Nt transmitters and Nr slowly moving receivers. The objective is that all receivers detect the transmitted signals, to estimate the time of arrival (TOA) and then to make possible the location with several TOA (more than 3). To use the CDMA (Code Division Multiple Access) modulation, specially adapted to our problem, we have to choose a method to generate a number Ns of broad-band signals. This study is devoted to the selection of Nt signals among the Ns. The aim is to choose the most distinctly detectable ones. Firstly, in a no Doppler context, the criterion of signals selection is based on a ratio between maximum of auto-correlation and cross-correlation. Secondly, in presence of Doppler, we rely on Ambiguity Function which allows representing the correlation function to several frequency Doppler shifts. The choice of Nt signals is then based on ratio between maximum of auto-ambiguity and cross-ambiguity. This paper will then highlight the interest of the criteria (correlation, ambiguity function) in the choice of the most appropriate signals in function of the multi-users context