For blind deconvolution of an unknown sparse sequence convolved with an unknown pulse, a powerful Bayesian method employs the Gibbs sampler in combination with a Bernoulli–Gaussian prior modeling sparsity. In this paper, we extend this method by introducing a minimum distance constraint for the pulses in the sequence. This is physically relevant in applications including layer detection, medical imaging, seismology, and multipath parameter estimation. We propose a Bayesian method for blind deconvolution that is based on a modified Bernoulli–Gaussian prior including a minimum distance constraint factor. The core of our method is a partially collapsed Gibbs sampler (PCGS) that tolerates and even exploits the strong local dependencies introduced by the minimum distance constraint. Simulation results demonstrate significant performance gains compared to a recently proposed PCGS. The main advantages of the minimum distance constraint are a substantial reduction of computational complexity and of the number of spurious components in the deconvolution result.

This paper presents a nonlinear mixing model for hyperspectral image unmixing. The proposed model assumes that the pixel reflectances are nonlinear functions of pure spectral components contaminated by an additive white Gaussian noise. These nonlinear functions are approximated using polynomial functions leading to a polynomial postnonlinear mixing model. A Bayesian algorithm and optimization methods are proposed to estimate the parameters involved in the model. The performance of the unmixing strategies is evaluated by simulations conducted on synthetic and real data.

Monitoring and detection of ships and oil spills using synthetic aperture radar (SAR) have received a considerable attention over the past few years, notably due to the wide area coverage and day and night all-weather capabilities of SAR systems. Among different polarimetric SAR modes, dual-pol SAR data are widely used for monitoring large ocean and coastal areas. The degree of polarization (DoP) is a fundamental quantity characterizing a partially polarized electromagnetic field, with significantly less computational complexity, readily adaptable for on-board implementation, compared with other well-known polarimetric discriminators. The performance of the DoP is studied for joint ship and oil-spill detection under different polarizations in hybrid/compact and linear dual-pol SAR imagery. Experiments are performed on RADARSAT-2 -band polarimetric data sets, over San Francisco Bay, and -band NASA/JPL UAVSAR data, covering the Deepwater Horizon oil spill in the Gulf of Mexico.

Wake vortices are associated to the generation of lift when an aircraft is flying. During the take-off and landing phases, wake vortices are hazardous if encountered by other flying aircrafts. In order to ensure flight safety and increase airports capacity as a constraining minimum distance between successive aircrafts has been defined to avoid them, wake vortex monitoring in real time has emerged as one of the key challenge in air traffic management. In this paper, the potential use of an X band Doppler radar for detecting and monitoring wake vortices in rainy weather is assessed by simulation. The Doppler signature measured by an X band radar in presence of a wake vortex in rainy weather is simulated accounting for the backscattering of each individual raindrop in the volume surrounding wake vortices.Starting from a given DSD and a homogeneous repartition of the raindrops in still air, their trajectory is computed assuming a generic air flow induced vortex and a simple model of drag. The descent velocity of the vortex due to the local reduction of buoyancy in the vortices is also taken into consideration in the computation of the trajectory. A scheme for computing the radar signals from the raindrops within wake vortices is described. The X band radar signatures in scanning mode are computed for raindrops in each concerned radar cell. According to the simulation results, the Doppler spectrum width of the raindrops disturbed by wake vortices is extended, thus providing a mean to identify the potential location of wake vortices in the scanned area and therefore to localize the hazards. The potentiality of this tool for the design of inversion algorithms from wake vortices signatures will also be addressed.

This article proposes a stochastic model to obtain the end-to-end delay law between two nodes of a Delay Tolerant Network (DTN). We focus on the commonly used Binary Spray and Wait (BSW) routing protocol and propose a model that can be applied to homogeneous or heterogeneous networks (i.e. when the inter-contact law parameter takes one or several values). To the best of our knowledge, this is the first model allowing to estimate the delay distribution of Binary Spray and Wait DTN protocol in heterogeneous networks. We first detail the model and propose a set of simulations to validate the theoretical results.

Electrical Flight Control Systems (EFCS) now constitute an industrial standard for commercial applications, ensuring a more sophisticated control of the aircraft and flight envelope protection functions. In the scope of a global optimization towards extended system availability and more easy-to-handle aircraft, sophisticated tools are necessary to diagnose sensor behaviour and to prevent from faulty measurements. In this context, a signal processing approach using Partial Least Squares (PLS) has been proposed to increase the EFCS autonomy. This algorithm establishes a linear relation between observed flight parameters - issued from possibly faulty sensors - and independent sensor measurements thanks to an iterative process. A monitoring strategy based on the regression coefficient dynamics, provided by the PLS, has been implemented and tested on real flight data and through an Airbus high-fidelity simulator, including realistic failure scenarios. The simulation results demonstrate the method performance robustness, in compliance with current real-time constraints. This paper focuses on the application of the method to the industrial context. A special attention is dedicated to the simulation process and to the performance analysis.

This paper addresses the problem of demodulating messages received by a low-orbit satellite (altitude between 700 and 800 km) and transmitted by vessels using the Automatic Identification System (AIS). AIS is a Self-Organized Time Division Multiple Access (SO-TDMA) system, in which vessels periodically transmit information (mainly including MMSI – identification code of the ship– and its GPS position). The main application of the actual AIS system is collision avoidance between ships but a satellite reception would lead to a global supervision of maritime traffic, which could be of great interest for a lot of applications (military but also civil applications as fleet surveillance and monitoring).

Periodic Nonuniform Sampling of order 2 (PNS2) is defined by two sequences with same period and some delay between them. PNS2 is known to suppress aliasing of multiband signals. Even if PNS2 reconstructs the signal by a linear combination of samples, the problem of retrieving a filtered version of the signal is more complicated. The simplest solution begins by a signal reconstruction through a sampling formula, followed by an analog filter. However new sampling formulas can solve this problem in a single stage. We give equivalent digital circuits which provide these formulas. Examples are provided, particularly when looking to retrieve subbands in communications.

Most of multipath multimedia streaming proposals use Forward Error Correction (FEC) approach to protect from packet losses. However, FEC does not sustain well burst of losses even when packets from a given FEC block are spread over multiple paths. In this article, we propose an online multipath convolutional coding for real-time multipath streaming based on an on-the-fly coding scheme called Tetrys. We evaluate the benefits brought out by this coding scheme inside an existing FEC multipath load splitting proposal known as Encoded Multipath Streaming (EMS). We demonstrate that Tetrys consistently outperforms FEC in both uniform and burst losses with EMS scheme. We also propose a modification of the standard EMS algorithm that greatly improves the performance in terms of packet recovery. Finally, we analyze different spreading policies of the Tetrys redundancy traffic between available paths and observe that the longer propagation delay path should be preferably used to carry repair packets.

In this paper, we introduce Multi-Slots Coded ALOHA (MuSCA) as a multiple random access method for satellite communications. This scheme can be considered as a generalization of the Contention Resolution Diversity Slotted Aloha (CRDSA) mechanism. Instead of transmitting replicas, this system replaces them by several parts of a single word of an error correcting code. It is also different from Coded Slotted ALOHA (CSA) as the assumption of destructive collisions is not adopted. In MuSCA, the entity in charge of the decoding mechanism collects all bursts of the same user (including the interfered slots) before decoding and implements a successive interference cancellation (SIC) process to remove successfully decoded signals. Simulations show that for a frame of 100 slots, the achievable total normalized throughput is greater than 1.25 and 1.4 for a frame of 500 slots, resulting in a gain of 80% and 75% with respect to CRDSA and CSA respectively. This paper is a first analysis of the proposed scheme and opens several perspectives.