This paper proposes a fast multi-band image fusion algorithm, which combines a high-spatial low-spectral resolution image and a low-spatial high-spectral resolution image. The well admitted forward model is explored to form the likelihoods of the observations. Maximizing the likelihoods leads to solving a Sylvester equation. By exploiting the properties of the circulant and downsampling matrices associated with the fusion problem, a closed-form solution for the corresponding Sylvester equation is obtained explicitly, getting rid of any iterative update step. Coupled with the alternating direction method of multipliers and the block coordinate descent method, the proposed algorithm can be easily generalized to incorporate prior information for the fusion problem, allowing a Bayesian estimator. Simulation results show that the proposed algorithm achieves the same performance as the existing algorithms with the advantage of significantly decreasing the computational complexity of these algorithms.

The installation of a condition monitoring system aims to reduce the operating costs of the monitored system by applying a predictive maintenance strategy. However, a system-driven configuration of the condition monitoring system requires the knowledge of the system kinematics and could induce lots a false alarms because of predefined thresholds. The purpose of this paper is to propose a complete data-driven method to automatically generate system health indicators without any a priori on the monitored system or the acquired signals. This method is composed of two steps. First, every acquired signal is analysed: the spectral peaks are detected and then grouped in more complex structure as harmonic series or modulation sidebands. Then, a time-frequency tracking operation is applied on all available signals: the spectral peaks and the spectral structures are tracked over time and grouped in trajectories, which will be used to generate the system health indicators. The proposed method is tested on real-world signals coming from a wind turbine test rig. The detection of a harmonic series and a modulation sideband reports the birth of a fault on the main bearing inner ring. The evolution of the fault severity is characterised by three automatically generated health indicators and is confirmed by experts.

We present a new delay-based transport protocol named FLOWER, that aims at providing a Lower-than-Best-Effort (LBE) service. The objective is to propose an alternative to the Low Extra Delay Background Transport (LEDBAT) widely deployed within the official BitTorrent client. Indeed, besides its intra-fairness problem, known as latecomer unfairness, LEDBAT can be too aggressive against TCP, making it ill suited for providing LBE services over certain networks such as constrained wireless networks. By using a fuzzy controller to modulate the sending rate, FLOWER aims to solve LEDBAT issues while fulfilling the role of a LBE protocol. Our simulation results show that FLOWER can carry LBE traffic in network scenarios where LEDBAT cannot while solving the latecomer unfairness problem. Finally, the presented algorithm is simple to implement and does not require complex computation that would prevent its deployment.

The use of optical communication to transfer data between LEO satellite and optical ground station is being studied. It creates the opportunities to highly increase a transmitted data rate across a free space. The optical propagation channel has specificities that imply the potential use of error correcting code (ECC) and interleaving at physical and higher layer. The study aims to assess the performance of a combination of ECC and interleaving in presence of various channel scenarios and receiver architectures. As a result of these studies, a functional physical layer simulator is provided. The simulator emulates a signal generation and applies time series representing the propagation channel with an effect of receiver front-ends. It also features various detection methods and computes mutual information (MI) in order to approximate ECC performances. A number of receiver architectures and channel scenarios were studied. The channel scenarios combine a direct coupling of the received signal into the photo-detector (PD) and among other assume the use of pre-amplified receiver implying the signal coupling into a standard single mode fiber (SSMF) prior to the detection. Time series were generated and represent the power received at PD input depending on the chosen scenarios (without adaptive optics (AO), with tip-tilt correction, with no dynamical coupling losses or with higher order AO correction). Two modulations of OOK and DBPSK along with various detection methods were examined. The tuning of ECC parameters was studied through the computation of mutual information. Additionally two cases of physical and higher layer interleaving were implemented providing an excellent diversity to the channel seen by the codeword of ECC. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

This Ph.D. thesis aims at evaluating the interest of using multivariate distributions for the analysis of heterogeneous images. The considered heterogeneous data are composed of images acquired by different sensors (including optical, radar and hyperspectral sensors) and possibly of an object database (containing roads, building, etc.). The applications considered in this thesis are mainly image registration, change detection and database updating. All these applications require to define a similarity measure between the different images or between features estimated from these images (called modalities).

Remote sensing images are images of the Earth surface acquired from satellites or airborne equipment. These images are beco-ming widely available nowadays, with many commercial and non-commercial services pro-viding them. The technology of the sensors required to capture this kind of images is evol-ving fast. Not only classical sensors are impro-ving in terms of resolution and noise level, but also new kinds of sensors are proving to be useful. Multispectral image sensors are stan-dard nowadays, synthetic aperture radar (SAR) images are very popular, and hyperspectral sen-sors are receiving more and more attention in many applications. One of the main applications of remote sensing images is the detection of changes in multitem-poral datasets, i.e., detecting changes in images of the same area acquired at different times. Change detection for images acquired by ho-mogeneous sensors has been of interest for a long time. However the wide range of different sensors found in remote sensing makes the de-tection of changes in images acquired by hete-rogeneous sensors an interesting challenge. The main interest of this thesis is to study statistical approaches to detect changes in images acquired by heterogeneous sensors.

L'utilisation des méthodes d'accès aléatoires basées sur le codage réseau couche physique ainsi que la suppression successive des interférences s'avère intéressante dans le monde des réseaux satellitaires. Des techniques telles que CRDSA et CSA proposées par l'ESA, ainsi que MuSCA proposée par l'ISAE permettent l'augmentation du débit et la réduction des délais sur un lien retour, par rapport aux méthodes d'accès aléatoires traditionnelles. Notre travail consiste à étudier les effets du canal de transmission sur ces méthodes et de proposer une amélioration de CRDSA au niveau du récepteur, appelée MARSALA. Les performances globales du système sont analysées en termes de taux d'erreur paquets et de débit obtenu à l'aide d'implémentations sur le simulateur de réseaux par satellite à Thales Alenia Space.

Nous commençons par une courte introduction des principes du positionnement GNSS précis par mesures de phase dites RTK (Real-Time Kinematic) et PPP (Precise Point Positioning). Ensuite nous présentons les résultats actuels du projet COPNAV en cours de l'action PTP de TESA. Le signal des satellites GNSS est poursuivi par des boucles à verrouillage de code, fréquence et phase. Les sorties utilisées pour le positionnement conventionnel sont celles fournies par la boucle de code. Pour le positionnement précis, on utilise les mesures de phase, moins bruitées et en particulier moins sensibles aux multitrajets. Ces mesures sont cependant difficiles d’exploitation à cause du nombre entier de cycle qu'il faut estimer (résolution d’ambiguïté), la phase étant mesurée à 2 près. Les méthodes de positionnement précis GNSS telles que RTK ou PPP se distinguent par les moyens et informations supplémentaires nécessaires à l’estimation des ambiguïtés et à la correction des mesures pour arriver à une précision centimétrique. Mais ces performances sont habituellement obtenues avec des récepteurs de haute qualité, dans des environnements dégagés. En environnements contraints (urbain, intérieur, etc.), la disponibilité du positionnement précis baisse considérablement du fait des fréquentes pertes de signal provoquant des sauts de cycle. Nous présenterons les principes de la technologie RTK et les résultats que nous avons obtenus en utilisant le logiciel RTKLIB avec un récepteur bas coût U-Blox NEO 7, dans des environnements contraints (urbain et urbain dense), associée à une méthode innovante de compensation des sauts de cycle.

Satellite telecommunications have seen a tremendous increase in interest, due to its ability to reduce the digital divide. In fact, a geostationary satellite can take advantage of its very wide coverage and high capacity to reach areas where deployment of a terrestrial network would not be possible, such as transports, or too expensive to be profitable, as in remote areas. Traditionally focused on digital television broadcasting, the latest generation of standards have evolved to reflect those new needs, dealing extensively with the transmission of interactive data, particularly by natively supporting Internet protocols. Scheduling has arisen as a major issue of those modern systems, since it has to deal with to highly uncorrelated processes : demand and capacity. Demand, on one side, evolves with user's needs, and therefore with the applications they are using : video, voice or data. Capacity, on the other side, depends on meteorological conditions over the satellite's cover, as the frequencies used in such systems are very sensitive to wet atmosphere attenuation. This thesis aims to study the problem of scheduling and resource allocation, hoping to achieve a service that can match with terrestrial networks in terms of services, while showing the best possible performances. If numerous solutions were proposed on this topic, none is taking into account all of the current system's constraints. In addition to the variable nature of system's capacity, the conjunction of variable demand and quality of service constraints constitutes an additional issue. Furthermore, we have to consider the practicability of our solution in a real-time context, necessary if we aim for industrial use. We have first developed a scheduler architecture for the Forward link, based on utility functions, thus allowing a simple formulation of the capacity versus demand compromise. We show, through a detailed low-complexity implementation and accurate simulations, how our algorithm could be used eciently in an industrial context. We then focus on the Return link, where we propose a resource allocation method, taking into account quality of service and quality of transmission jointly to deliver an ecient yet consistent resource allocation. Simulations show that our algorithm achieves a better efficiency and traffic handling than reference solutions presented in the literature.

Satellite telecommunications have seen a tremendous increase in interest, due to its ability to reduce the digital divide. In fact, a geostationary satellite can take advantage of its very wide coverage and high capacity to reach areas where deployment of a terrestrial network would not be possible, such as transports, or too expensive to be profitable, as in remote areas. Traditionally focused on digital television broadcasting, the latest generation of standards have evolved to reflect those new needs, dealing extensively with the transmission of interactive data, particularly by natively supporting Internet protocols. Scheduling has arisen as a major issue of those modern systems, since it has to deal with to highly uncorrelated processes : demand and capacity. Demand, on one side, evolves with user's needs, and therefore with the applications they are using : video, voice or data. Capacity, on the other side, depends on meteorological conditions over the satellite's cover, as the frequencies used in such systems are very sensitive to wet atmosphere attenuation. This thesis aims to study the problem of scheduling and resource allocation, hoping to achieve a service that can match with terrestrial networks in terms of services, while showing the best possible performances. If numerous solutions were proposed on this topic, none is taking into account all of the current system's constraints. In addition to the variable nature of system's capacity, the conjunction of variable demand and quality of service constraints constitutes an additional issue. Furthermore, we have to consider the practicability of our solution in a real-time context, necessary if we aim for industrial use. We have first developed a scheduler architecture for the Forward link, based on utility functions, thus allowing a simple formulation of the capacity versus demand compromise. We show, through a detailed low-complexity implementation and accurate simulations, how our algorithm could be used efficiently in an industrial context. We then focus on the Return link, where we propose a resource allocation method, taking into account quality of service and quality of transmission jointly to deliver an efficient yet consistent resource allocation. Simulations show that our algorithm achieves a better efficiency and traffic handling than reference solutions presented in the literature.