The evolution of wireless communications systems have enabled to consider many applications for Intelligent Transportation Systems (ITS). They may or may not use the infrastructure. They will consider from the traffic safety applications up to the driver’s comfort or network games. The map updates are, from our point of view, a representative application but in the other hand it can help to reduce congestion in improving efficiency in decision making. It has well-defined characteristics : high volume of data, low delay constraint, possibility of implementation of infrastructure-to-vehicle communications, between vehicles and hybrids. The objective is that the contents are fully downloaded by all vehicles in minimum time, using fewer resources and lower costs. The solutions that have emerged as the most suitable concerned the use of the technology 802.11p with or without infrastructure. In the case of solutions with infrastructure, a number of access points broadcast information with coverage areas most often disjointed. Given the size of area used and/or flow devoted to this type of applications, the transition to a single access point is not enough to download these maps. It is then to define strategies of information dissemination. A first study was to compare a unicast strategy face to broadcast/multicast strategy. The latter appears largely improved. A combination of these principles does not improve system performance, because the flow devoted to unicast transmission does not compensate for the flow not used by the broadcast. The problem is duplicate chunks received by vehicles passing from several consecutive access points. To mitigate the phenomenon of duplication, we used the linear network coding pseudorandom. The idea is that the access point broadcasts linear combinations of chunks of files. The large number of these linear combinations significantly reduces this phenomenon. In a complementary manner, we investigated the use of ad hoc communications to fill the missing chunks of file, particularly in the absence of infrastructure. We verified that we could achieve good results in this context based on the diversity of chunks of files which are owned by the encountered vehicles.

The evolution of wireless communications systems have enabled to consider many applications for Intelligent Transportation Systems (ITS). They may or may not use the infrastructure. They will consider from the traffic safety applications up to the driver’s comfort or network games. The map updates are, from our point of view, a representative application but in the other hand it can help to reduce congestion in improving efficiency in decision making. It has well-defined characteristics : high volume of data, low delay constraint, possibility of implementation of infrastructure-to-vehicle communications, between vehicles and hybrids. The objective is that the contents are fully downloaded by all vehicles in minimum time, using fewer resources and lower costs. The solutions that have emerged as the most suitable concerned the use of the technology 802.11p with or without infrastructure. In the case of solutions with infrastructure, a number of access points broadcast information with coverage areas most often disjointed. Given the size of area used and/or flow devoted to this type of applications, the transition to a single access point is not enough to download these maps. It is then to define strategies of information dissemination. A first study was to compare a unicast strategy face to broadcast/multicast strategy. The latter appears largely improved. A combination of these principles does not improve system performance, because the flow devoted to unicast transmission does not compensate for the flow not used by the broadcast. The problem is duplicate chunks received by vehicles passing from several consecutive access points. To mitigate the phenomenon of duplication, we used the linear network coding pseudorandom. The idea is that the access point broadcasts linear combinations of chunks of files. The large number of these linear combinations significantly reduces this phenomenon. In a complementary manner, we investigated the use of ad hoc communications to fill the missing chunks of file, particularly in the absence of infrastructure. We verified that we could achieve good results in this context based on the diversity of chunks of files which are owned by the encountered vehicles.

This paper addresses the problem of ship localization by using the messages received by satellites and transmitted by the automatic identification system (AIS). In particular, one considers the localization of ships that do not transmit their actual position in AIS signals. The proposed localization method is based on the least squares algorithm and uses the differences of times of arrival and the carrier frequencies of the messages received by satellite. A modification of this algorithm is proposed to take into account the displacement model of the ships as additional measurements. This modification shows a significant localization improvement.

Delay/Doppler radar altimetry has been receiving an increasing interest, especially since the launch of the first altimeter in 2010 . It aims at reducing the measurement noise and increasing the along-track resolution in comparison with conventional pulse limited altimetry. A semi-analytical model was recently introduced for this new generation of delay/Doppler altimeters. The first contribution of this paper is the derivation of the Cram´er-Rao bounds (CRBs) associated with the parameters of this recent delay/Doppler model. These bounds are then compared with those obtained for conventional altimetry. The second contribution of this paper is the derivation of a new weighted least squares estimator based on the semianalytical delay/Doppler model. The performance of this estimator is very promising when compared to other more classical estimators and to the corresponding CRBs.

We develop a parametric high-resolution method for the estimation of the frequency nodes of linear combinations of complex exponentials with exponential damping. We use Kronecker’s theorem to formulate the associated nonlinear least squares problem as an optimization problem in the space of vectors generating Hankel matrices of fixed rank. Approximate solutions to this problem are obtained by using the alternating direction method of multipliers. Finally, we extract the frequency estimates from the con-eigenvectors of the solution Hankel matrix. The resulting algorithm is simple, easy to implement and can be applied to data with equally spaced samples with approximation weights, which for instance allows cases of missing data samples. By means of numerical simulations, we analyze and illustrate the excellent performance of the method, attaining the Cramér-Rao bound.

On considère un réseau de radars MIMO dont on cherche à déterminer la meilleure répartition de largeurs de bande et de puissance entre les différentes antennes émettrices en vue d’obtenir une certaine précision de la localisation d’une cible unique. Plus précisément, on s’intéresse ici à l’allocation optimale de bande seule, ainsi qu’à l’allocation optimale conjointement de bande et de puissance. Cette allocation s’effectue par la minimisation de la borne de Cramér-Rao. Le problème d’optimisation non-convexe obtenu est résolu par un algorithme de programmation par différence de fonctions convexes. Les résultats numériques montrent que l’allocation conjointe fournit les meilleures performances, et que d’autre part l’allocation de bande joue un rôle prépondérant dans ces performances. De plus, une borne inférieure sur la borne de Cramér-Rao optimale théorique, difficilement calculable, a également été définie, qui montre la qualité de la solution quasi-optimale.

This paper presents a demodulation algorithm for automatic identification system (AIS) signals received by a satellite. The main contribution of this work is to consider the phase recovery problem for an unknown modulation index, coupled with a time-varying phase shift. The proposed method is based on a demodulator introduced in a previous paper based on a Viterbi-type algorithm applied to an extended trellis. The states of this extended trellis are composed of a trellis-code state and of a cyclic redundancy check state. The bit stuffing mechanism is taken into account by defining specific conditional transitions in the extended trellis. This algorithm estimates and tracks the phase shift by modifying the Euclidean distance used in the trellis. Simulation results obtained with and without phase tracking are presented and compared in the context of the AIS system.

This work addresses the problem of reconstruction of spectra F(ω) from the irregular sampling of autocorrelation functions f(t). We assume that F(ω) has bounded support [-π, π] : The number 2L of sampling times is such that the variation of F(ω) on intervals of length π/L is small enough to lead to a good interpolation of this function. Reconstruction formulas are based on PNS (Periodic Nonuniform Sampling) plans. They allow reconstructions not demanding periodic resampling and suppress two stages in classical computations. The method can also be easily generalized to spectra in symmetric frequency bands (bandpass signals).

The concept of delay/Doppler radar altimeter has been under study since the mid 90’s, aiming at reducing the measurement noise (by increasing the number of observations) and increasing the along-track resolution (by using the information of the Doppler frequency) in comparison with the conventional pulse limited altimeters. This paper introduces a semi-analytical model for delay/Doppler altimetry. The performance of the proposed model and the resulting estimation strategy are evaluated via simulations conducted on synthetic and real data. A comparison between conventional altimetry and delay/Doppler altimetry provides very promising results in favor of the proposed model.