The pseudo maximum likelihood estimator allows one to estimate the unknown parameters of Brown’s model for altimeter wave- forms. However, the optimality of this estimator, for instance in terms of minimizing the mean square errors of the unknown para- meters is not guarantied. Thus it is not clear whether there is some space for developing new estimators for the unknown parameters of altimetric signals. This paper derives the Crame ́r-Rao lower bounds of the parameters associated to Brown’s model. These bounds provide the minimum variances of any unbiased estima- tor of these parameters, i.e. a reference in terms of estimation er- ror. A comparison between the mean square errors of the standard estimators and Crame ́r-Rao bounds allows one to evaluate the po- tential gain (in terms of estimation variance) that could be achieved with new estimation strategies.

Several telemedicine applications are proposed within the frame of OURSES project, French acronym for Offer of Rural Use of Services by Satellite, providing services for elderly people. The main objective of this project is to show the interest of using satellites as a complement to terrestrial technologies, in areas where telecommunication infrastructure is lacking or incomplete. This paper describes one of these applications: an ECG monitoring system. This telemonitoring system allows, thanks to a wireless wearable sensor, to detect possible cardiac problems of elderly people. ECG signals are analyzed through signal processing algorithms and if some abnormal condition is detected, an alarm is raised and sent via satellite to the physician's office. The corresponding physician is able to access at any time the recorded ECG signals, whenever he is willing to, in the presence of an alarm or not. This allows a constant monitoring of the elderly people. Tests realized in a real environment have demonstrated the feasibility and the interest of this application.

This paper addresses the problem of classifying altimetric waveforms backscattered from different kinds of surfaces including oceans, ices, deserts and forests. Appropriate features associated with altimetric radar waveforms are first introduced for this classification. These features are completed by radiometer temperatures and pre-processed using a linear discriminant analysis for dimensionality reduction. The classification of altimetric waveforms is finally achieved using the resulting pre-processed vector with reduced dimension. Different classification strategies are finally considered. These strategies are based on the nearest mean rule, the nearest neighbor method or on the multilayer perceptron. Various simulation results illustrate the performance of the proposed classifier.

This paper studies a Bayesian algorithm for estimating the parameters associated to Brown's model. The joint posterior distribution of the unknown parameter vector (amplitude, epoch and significant wave height) associated with this model is derived. This posterior is too complex to obtain closed form expressions of the minimum mean square error and the maximum a posteriori estimators. We propose to sample according to this distribution using an hybrid Metropolis within Gibbs algorithm. The simulated samples are then used to estimate the unknown parameters of Brown's model. The proposed strategy provides better estimations than the standard maximum likelihood estimator at the price of an increased computational cost.

Assessing the quality of a hyperspectral image is a difficult task. However, this assessment is required at different levels of the instrument design: evaluation of the signal to noise ratio necessary for a particular application, determining the acceptable level of losses from compression algorithms for example. It has been shown previously that a combination of five quality criteria can provide a good evaluation of the impact of some degradation on applications, such as classification algorithms for example. This paper refines this concept, providing a representation of the degradation which allows predicting the impact on applications.

The current Transformation of the military networks adopts the MANET as a main component of the tactical domain. Indeed, a MANET is the right solution to enable highly mobile, highly reactive and quickly deployable tactical networks. Many applications such as the Situational Awareness rely on group communications, underlying the need for a multicast service within the tactical environment where the MANET is employed as a transit network. The purpose of this thesis is to study the setting up of an optimal multicast service within this tactical environment. We firstly focus on defining the protocol architecture to carry out within the tactical network paying particular attention to the MANET. This network is interconnected with different types of networks based on IP technologies and implementing poten- tially heterogeneous multicast protocols. The tactical MANET is supposed to be made of several hundred of mobile nodes, which implies that the scalability is cru- cial in the multicast protocol architecture choice. Since the concept of clustering proposes interesting scalability features, we consider that the MANET is a clus- tered network. Thereby, we define two multicast routing protocols adapted to the MANET: firstly STAMP that is in charge of the multicast communications within each cluster and secondly SAFIR that handles multicast flows between the clusters. These two protocols that can be implemented independently, act in concert to pro- vide an efficient and scalable multicast service for the tactical MANET. Then, we study the interoperability of these multicast protocols employed within the MANET with those employed in the heterogeneous networks that it is interconnected with in order to guarantee end-to-end seamless multicast services to users. Finally, since the multicast protocols proposed in this thesis rely on underlying unicast routing protocols, we propose, in the last chapter, a scalable unicast routing protocol based on OLSR.

Current satellite architectures for delivering interactive IP services and broadband connectivity are based on the layered principles of the OSI reference model. There is no denying that the traditional research approach focusing on layer-specific problems faced by satellite architectures within the well-defined bounds of the layered model has been rather fruitful. Wireless-friendly adaptations of major protocols exist today, and state-of-the-art coding and modulation techniques have taken physical layers close to their theoretical performance limits. However, a number of critical issues such as end-to-end fulfillment of service-level agreements, seamless mobility or scalable support for reliable multicast have not yet found optimal solutions by means of independent layer tuning, due to the unique characteristics of satellite links. The modular approach blurs the dynamics of layers interaction with the wireless medium, hindering the overall system performance with redundancy, inefficient resource handling and suboptimal performances. Recent research has thus started to address these problems in a holistic way, by stressing the potential benefits of authorizing information exchanges across layers beyond the scope of the reference model. Multi-layers feedback and the resulting system adaptivity offer multiple possibilities for attuning the protocol stack as a whole, allowing for overall optimization and better integration of satellite links in the increasingly heterogeneous network environment. Cross-layer design has emerged as a promising research area in the satellite and wireless communications fields, characterized by a multi-disciplinary approach involving information theory, network protocol design, optimization techniques, stochastic modeling and advanced signal processing. Since recent crosslayer proposals have started tackling successfully some complex problems that layered architectures do not address properly, next-generation standards and protocols are starting to integrate crosslayer principles de facto. This thesis addresses the error control problem for satellite links from the perspective of cross-layer design. At the crossroads of QoS-related constraints, devices complexity and efficient spectrum use, error control is indeed a key aspect of wireless communications — particularly crucial in the satellite context — where cross-layer enhancements can play an important role. After a thorough introduction to cross-layer design, the first part of this work focuses specifically on the error control strategy of early DVB satellites, where redundancies between the channel decoder and the adaptation layers are set to light in order to propose a joint bandwidth-efficient error control policy. The focus then moves to second-generation DVB satellites and the definition of the novel, IPcentric and cross-layer friendly GSE encapsulation protocol, where results from the aforementioned study were successfully applied. Finally, a whole new cross-layer framework called HERACLES is introduced, offering efficient and overhead-free error correction capabilities for almost any layer of a protocol stack and being patented at the moment of writing these words. The results of the overall work show the strengths of an integrated approach to error control, and open the way for innovative cross-layer mechanisms to be deployed in next-generation communications networks.

In this paper, we introduce a new approach for the acquisition of weak GNSS signals. For the GPS L1 signal, we utilize the replication property of the C/A code within each data bit to introduce a block averaging pre-processing (BAP) approach for improving receiver robustness against undesired signals. A large number of weighted signal blocks is coherently accumulated and synchronously averaged to obtain a single block with improved signal power. We present several properties of the proposed GNSS signals enhancement technique and we analyze its robustness against noise and different classes of interferers. Thus, we develop a software defined acquisition procedure using the efficient FFT correlation approach. We propose two acquisition algorithms based on the BAP approach. The first scheme implements the parallel code phase search in finding the 2-D spectrum peak using circular cross-correlations. In the second scheme, we exploit the BAP for a fast acquisition performing the frequency estimation prior to the 1-D code-phase search.

In this paper, a way of improving the positioning performance of the GNSS system through hybridization with distances derived from GSM power measurements was proposed. The GNSS/GSM Fusion algorithm was an APF (Auxiliary Particle Filter) algorithm with UKF (Unscented Kalman Filter) proposal and Rao-Blackwellisation allowing tight hybridization of GPS and GSM measurements. Scenario 1 and 2 showed an improvement in terms of accuracy and availability thanks to the use of GSM received powers in addition to GPS pseudoranges in a realistic scenario. Several perspectives can be given: First, the automatic estimation of hyperparameters: PF algorithms can be used to perform joint estimation of some global parameters (as for instance observation and evolution noises variances). This would give the fusion algorithm a better adaptability to local situations. Finally, the use of “multiple models” formulation can be envisaged: ability of PF algorithms to select automatically the most adapted model among a bank of available evolution and observation models. This would allow the algorithm to deal better with multipath effects.