The Maseng-Bakken model has shown interesting properties to model rain attenuation for Ka and Q/V broadband satellite systems. This paper derives the optimal rain attenuation predictor based on the Maseng-Bakken model. The optimal predictor is obtained by minimizing the mean square error between the rain attenuation and its estimate. We show that this predictor reduces to a bank of filters whose parameters depend on the rain attenuation power spectral density. Simulation results allow us to appreciate the performance of the resulting rain attenuation prediction that is compared with more traditional strategies.

In this paper, we propose to extend the WAVE Architecture with satellite, WiFi andcellular technologies. Many applications can be considered in vehicular networks whichcan be provided through one or several communication systems. In this paper, the mapupdate application has been considered over different technologies. Simulations were runusing NS3 simulator to compare the behavior of files downloads with 802.11p and with othertechnologies. The aim is to optimize the necessary amount of resource, and to determinethe best combination of technologies to download maps.

In acoustic, ultrasonic or electromagnetic propagation, crossed media are often modelled by linear filters with complex gains in accordance with the Beer-Lambert law. This paper addresses the problem of propagation in media where polarization has to be taken into account. Because waves are now bi-dimensional, an unique filter is not sufficient to represent the effects of the medium. We propose a model which uses four linear invariant filters, which allows to take into account exchanges between components of the field. We call it bi-filter because it has two inputs and two outputs. Such a circuit can be fitted to light devices like polarizers, rotators and compensators and to propagation in free space. We give a generalization of the Beer-Lambert law which can be reduced to the usual one in some cases and which justifies the proposed model for propagation of electromagnic beams in continuous media.

This paper addresses the problem of classifying altimetric signals according to their shapes. The proposed classifier is divided into three steps. A one-class support vector machine method is first used to isolate the large amount of Brown-like echoes from others signals which are considered as outliers. The second step extracts pertinent features from the the remaining echoes (which cannot be well described by the Brown model). These features are projected onto discriminant axes using linear discriminant analysis. The final step classifies the projected feature vectors using a standard Bayesian classifier. The proposed three step classification strategy is evaluated on supervised real altimetric echoes.

In this paper, we investigate the application of multiuser detection techniques to a Low Polar Orbit (LPO) mobile satellite used in the ARGOS system. These techniques are used to mitigate the multiple access interference in the uplink transmission of the system. Unlike CDMA, due to the Doppler Effect, each signal has a different received carrier frequency and a different propagation delay. Multiuser detection techniques are proposed for asynchronous transmission in ARGOS system: the maximum likelihood detector, the conventional detector, and the sequential interference cancellation detector, as solutions to tackle the interference effects. Bit Error Rate performance graphs are shown for these techniques.

This paper studies a new Bayesian unmixing algorithm for hyperspectral images. Each pixel of the image is modeled as a linear combination of so-called endmembers. These endmembers are supposed to be random in order to model uncertainties regarding their knowledge. More precisely, we model endmembers as Gaussian vectors whose means have been determined using an endmember extraction algorithm such as the famous N-finder (N-FINDR) or Vertex Component Analysis (VCA) algorithms. This paper proposes to estimate the mixture coefficients (referred to as abundances) using a Bayesian algorithm. Suitable priors are assigned to the abundances in order to satisfy positivity and additivity constraints whereas conjugate priors are chosen for the remaining parameters. A hybrid Gibbs sampler is then constructed to generate abundance and variance samples distributed according to the joint posterior of the abundances and noise variances. The performance of the proposed methodology is evaluated by comparison with other unmixing algorithms on synthetic and real images.

In condition monitoring a part of the information necessary for decision-making comes from scrutinizing a time measure or a transform of this measure. Frequency domain is commonly exploited; lag domain is not, albeit advantages of the autocorrelation function have long been known. In this paper, we dwell on the autocorrelation function in order to extract some interesting properties of the measure. We propose two indicators in order to characterize the periodicity of a signal. First is based on the non-biased autocorrelation function and indicates a fundamental periodicity rate. Second is based on the biased autocorrelation and gives a dominant-power periodicity rate. The study of the 2Dplane defined by these two indicators allows the definition of regions attached to one type of periodicity from periodic to aperiodic through almost-periodic and quasi-periodic. Combined with an estimation of the correlation support, a final decision about the periodicity of the signal is given. In case of a periodic signal, a way of estimating the global signal ratio is proposed. These new outputs are valuable for initializing more complex processing. All the algorithms proposed are fully automatic, one click use! Relevance of these indicators is shown on real-world signals, current and vibration measures mainly.

Periodic nonuniform sampling of second order (PNS2) involves two periodic sequences with the same period. This sampling scheme has been shown to remove aliasing. Moreover, under particular conditions on their spectral band (or spectral support), exact reconstruction of functions can be derived from their PNS2. This paper more generally deals with the best mean-square interpolation for stationary processes with any known power spectrum, from PNS2 and, possibly, with aliasing. We show that the best estimation is based upon particular linear filters, which depend on the gap between both sampling sequences. The mean-time error also depends on this gap. The errorless interpolation is a particular case. It requires the knowledge of the spectral support rather than the power-spectrum values.

Space Vehicle (SV) life span depends on its station keeping capability. Station keeping is the ability of the vehicle to maintain position and orientation. Due to external perturbations, the trajectory of the SV derives from the ideal orbit. Actual positioning systems for satellites are mainly based on ground equipment, which means heavy infrastructures. Autonomous positioning and navigation systems using Global Navigation Satellite Systems (GNSS) can then represent a great reduction in platform design and operating costs. Studies have been carried out and the first operational systems, based on GPS receivers, become available. But better availability of service could be obtained considering a receiver able to process GPS and Galileo signals. Indeed Galileo system will be compatible with the current and the modernized GPS system in terms of signals representation and navigation data. The greater availability obtained with such a receiver would allow significant increase of the number of point solutions and performance enhancement. For a mid-term perspective Thales Alenia Space finances a PhD to develop the concept of a reconfigurable receiver able to deal with both the GPS system and the future Galileo system. In this context, the aim of this paper is to assess the performances of a receiver designed for Geosynchronous Earth Orbit (GEO) applications. It is shown that high improvements are obtained with a receiver designed to track both GPS and Galileo satellites. The performance assessments have been used to define the specifications of the future satellite GNSS receiver.