We present a solution to evaluate the performance of transport protocols as a function of link layer reliability schemes (i.e. ARQ, FEC and Hybrid ARQ) applied to satellite physical layer traces. As modelling such traces is complex and may require approximations, the use of real traces will minimise the potential for erroneous performance evaluations resulting from imperfect models. Our Trace Manager Tool (TMT) produces the corresponding link layer output, which is then used within the ns-2 network simulator via the additionally developed ns-2 interface module. We first present the analytical models for the link layer with bursty erasure packets and for the link layer reliability mechanisms with bursty erasures. Then, we present details of the TMT tool and our validation methodology, demonstrating that the selected performance metrics (recovery delay and throughput efficiency) exhibit a good match between the theoretical results and those obtained with TMT. Finally, we present results showing the impact of different link layer reliability mechanisms on the performance of TCP Cubic transport layer protocol.

We propose a novel DTN routing algorithm, called DQN, specifically designed for quasi-deterministic networks with an application to satellite constellations. We demonstrate that our proposal efficiently forwards the information over a satellite network derived from the Orbcomm topology while keeping a low replication overhead. We compare our algorithm against other well-known DTN routing schemes and show that we obtain the lowest replication ratio without the knowledge of the topology and with a delivery ratio of the same order of magnitude than a reference theoretical optimal routing.

This paper addresses the problem of error correction in a multi-user trellis coded system in the presence of bit stuffing. In particular, one considers the situation in which automatic identification system (AIS) signals are received by a satellite. The proposed receiver uses a cyclic redundancy check (CRC) for error correction. A Viterbi algorithm based on a so-called extended trellis is developed. This trellis is defined by extended states composed of a trellis-code state and a CRC state. Moreover, special conditional transitions are defined in order to take into account the possible presence of bit stuffing. The proposed algorithm was first developed in a single-user context. It is generalized in this paper to a multi-user scenario by designing an interference mitigation method. This method allows one to derive a demodulation algorithm whose complexity is almost identical to that obtained in the single-user context. Some performance results are presented in the context of AIS and compared with results provided by existing techniques.

The delineation of P and T waves is important for the interpretation of ECG signals. In this work, we propose a sequential Bayesian detection-estimation algorithm for simultaneous P and T wave detection, delineation, and waveform estimation on a beat-to-beat basis. Our method is based on a dynamic model which exploits the sequential nature of the ECG by introducing a random walk model to the waveforms. The core of the method is a marginalized particle filter that efficiently resolves the unknown parameters of the dynamic model. The proposed algorithm is evaluated on the annotated QT database and compared with state-of-the-art methods. Its on-line characteristic is ideally suited for real-time ECG monitoring and arrhythmia analysis.

Global aircraft optimization is a main concern for future and upcoming programs. In particular, great research efforts are dedicated to Electrical Flight Control Systems (EFCS). Obviously, their reliability increases with the redundancy of the flight parameter sensors. However, physical redundancy, obtained by increasing the number of sensors, penalizes the aircraft weight and cost. This paper proposes a sensor failure detection method based on analytic redundancy. The flight parameter of interest is modelled as a linear function of independent sensor measurements on a sliding observation window. The Partial Least Squares (PLS) algorithm is used to estimate regression coefficients on this window. The PLS computes the solution via an iterative processing, and thus can be implemented in the flight control computer for a real time use. Two different failure detection strategies based on the behaviour of the regression coefficients are proposed. Simulation results show that the proposed method leads to robust detections.

In numerous applications, it is required to estimate the principal subspace of the data, possibly from a very limited number of samples. Additionally, it often occurs that some rough knowledge about this subspace is available and could be used to improve subspace estimation accuracy in this case. This is the problem we address herein and, in order to solve it, a Bayesian approach is proposed. The main idea consists of using the CS decomposition of the semi-orthogonal matrix whose columns span the subspace of interest. This parametrization is intuitively appealing and allows for non informative prior distributions of the matrices involved in the CS decomposition and very mild assumptions about the angles between the actual subspace and the prior subspace. The posterior distributions are derived and a Gibbs sampling scheme is presented to obtain the minimum mean-square distance estimator of the subspace of interest. Numerical simulations and an application to real hyperspectral data assess the validity and the performances of the estimator.

This paper addresses the problem of jointly estimating the statistical distribution and segmenting lesions in multiple-tissue high-frequency skin ultrasound images. The distribution of multiple-tissue images is modeled as a spatially coherent Þnite mixture of heavy-tailed Rayleigh distributions. Spatial coherence inherent to biological tissues is modeled by enforcing local dependence between the mixture components. An original Bayesian algorithm combined with a Markov chain Monte Carlo method is then proposed to jointly estimate the mixture parameters and a label-vector associating each voxel to a tissue. More precisely, a hybrid Metropolis-within-Gibbs sampler is used to draw samples that are asymptotically distributed according to the posterior distribution of the Bayesian model. The Bayesian estimators of the model parameters are then computed from the generated samples. Simulation results are conducted on synthetic data to illustrate the performance of the proposed estimation strategy. The method is then successfully applied to the segmentation of in vivo skin tumors in high-frequency 2-D and 3-D ultrasound images.

Road maps are important for several applications in vehicular networks. As a consequence, an updated map is essential for a proper behavior of such applications. In this paper, we focus on a map update application based on an infrastructure-to-vehicle communication with a high mobility. In order to understand the application's behavior, we analyze different performance criteria: System Goodput, Packet Delivery Ratio, Delay, Fairness, and Fragmentation. We compare the application's QoS behavior with three different flow densities (overloaded system, maximum system capacity, and under saturated system) and determinate a trade off between bandwidth (spectrum efficiency) and performance.

Here the concept of Doppler information geometry is summarized and introduced to evaluate the richness of Doppler velocity components of radar signal and applied for wake turbulence monitoring. With the methods of information geometry, we consider all the Toeplitz Hermitian Positive Definite covariance matrices of order n as a manifold Ωn . Geometries of covariance matrices based on two kinds of radar data models are presented. Finally, a radar detector based on Doppler entropy assessment is analyzed and applied for wake turbulence monitoring. This advanced Doppler processing chain is also implemented by CUDA codes for GPU parallel computation.

Space Wire is a standard of on-board networks for satellites promoted by the ESA. As the ESA plans to use Space Wire as the sole network for both critical and non-critical traffics, network designers need tools to check that all the critical messages meet their deadlines. We previously proposed two such tools to compute an upper-bound on the worst-case end-to-end delay of a packet traversing a Space Wire network. The main contribution of this paper is the comparison of those two methods on a network configuration provided by Thales Alenia Space that is representative of next generation large satellites. The goal is to identify the key parameters that affect the bounds computed by the methods. We then conduct a sensitivity analysis on simpler network configurations to study the impact of those parameters on the methods and determine which method works better in different situations.