A. Quinquis

Bio: A. Quinquis is an academic researcher. The author has contributed to research in topics: Channel (broadcasting) & Communication channel. The author has an hindex of 2, co-authored 2 publications receiving 19 citations.

A time-frequency approach to blind deconvolution in multipath underwater channels

Abstract: Blind deconvolution is presented in the underwater acoustic channel context, by time-frequency processing. The acoustic propagation environment was modelled as a multipath propagation channel. For noiseless simulated data, source signature estimation was performed by a model-based method. The channel estimate was obtained via a time-frequency formulation of the conventional matched-filter. Simulations used a ray-tracing physical model, initiated with at-sea recorded environmental data, in order to produce realistic underwater channel conditions. The quality of the estimates was 0.793 for the source signal, and close to 1 for the resolved amplitudes and time-delays of the impulse response. Time-frequency processing has proved to overcome the typical ill-conditioning of single sensor deterministic deconvolution techniques.

Blind deconvolution for robust signal estimation and approximate source localization.

Abstract: Synthetic time reversal (STR) is a technique for blind deconvolution in an unknown multipath environment that relies on generic features (rays or modes) of multipath sound propagation This paper describes how ray-based STR signal estimates may be improved and how ray-based STR sound-channel impulse-response estimates may be exploited for approximate source localization in underwater environments Findings are based on simulations and underwater experiments involving source-array ranges from 100 m to 1 km in 60 -m-deep water and chirp signals with a bandwidth of 15–40 kHz Signal estimation performance is quantified by the correlation coefficient between the source-broadcast and the STR-estimated signals for a variable number N of array elements, 2 ≤ N ≤ 32, and a range of signal-to-noise ratio (SNR), −5 dB ≤ SNR ≤ 30 dB At high SNR, STR-estimated signals are found to have cross-correlation coefficients of ∼90% with as few as four array elements, and similar performance may be achieved at a SNR of near

Broadband sparse-array blind deconvolution using frequency-difference beamforming

Abstract: Synthetic time reversal (STR) is a technique for blind deconvolution of receiving-array recordings of sound from an unknown source in an unknown multipath environment. It relies on generic features of multipath sound propagation. In prior studies, the pivotal ingredient for STR, an estimate of the source-signal's phase (as a function of frequency ω), was generated from conventional beamforming of the received-signal Fourier transforms, Pj(ω), 1 ≤ j ≤ N, where N is the number of array elements. This paper describes how STR is implemented even when the receiving-array elements are many wavelengths apart and conventional beamforming is inadequate. Here, the source-signal's phase is estimated by beamforming Pj*(ω1)Pj(ω2) at the difference frequency ω2 − ω1. This extension of STR is tested with broadband signal pulses (11–19 kHz) and a vertical 16-element receiving array having a 3.75-m-spacing between elements using simple propagation simulations and measured results from the FAF06 experiment involving 2.2 km...

Blind separation of underwater acoustic signals

Abstract: In last two decades, many researchers have been involved in acoustic tomography applications. Recently, few algorithms have been dedicated to the passive acoustic tomography applications in a single input single output channel. Unfortunately, most of these algorithms can not be applied in a real situation when we have a Multi-Input Multi-Output channel. In this paper, we propose at first a realistic model of an underwater acoustic channel, then a general structure to separate acoustic signals crossing an underwater channel is proposed. Concerning ICA algorithms, many algorithms have been implemented and tested but only two algorithms give us good results. The latter algorithms minimize two different second order statistic criteria in the frequency domain. Finally, some simulations have been presented and discussed.

A time-frequency approach to blind deconvolution in multipath underwater channels

Abstract: Blind deconvolution is presented in the underwater acoustic channel context, by time-frequency processing. The acoustic propagation environment was modelled as a multipath propagation channel. For noiseless simulated data, source signature estimation was performed by a model-based method. The channel estimate was obtained via a time-frequency formulation of the conventional matched-filter. Simulations used a ray-tracing physical model, initiated with at-sea recorded environmental data, in order to produce realistic underwater channel conditions. The quality of the estimates was 0.793 for the source signal, and close to 1 for the resolved amplitudes and time-delays of the impulse response. Time-frequency processing has proved to overcome the typical ill-conditioning of single sensor deterministic deconvolution techniques.

Influence de la non-stationnarité du milieu de propagation sur le processus de Retournement Temporel (RT)

Abstract: Cette these a pour objectif la quantification de l’impact d’incertitudes affectant le processus de Retournement Temporel (RT) Ces aleas, de natures diverses, peuvent avoir une forte influence s’ils se produisent entre les deux etapes du RT Dans cette optique la methode de Collocation Stochastique (CS) est utilisee Les tres bons resultats en termes d’efficacite et de precision observes lors de precedentes etudes en Compatibilite ElectroMagnetique (CEM) se confirment ici, pour des problematiques de RT Cependant, lorsque la dimension du probleme a traiter augmente (nombre de variables aleatoires important), la methode de CS atteint ses limites en termes d’efficacite Une etude a donc ete menee sur les methodes d’Analyse de Sensibilite (AS) qui permettent de determiner les parts d’influence respectives des entrees d’un modele Parmi les differentes techniques quantitatives et qualitatives, la methode de Morris et un calcul des indices de Sobol totaux ont ete retenus Ces derniers apportent des resultats qualitatifs a moindre frais, car seule une separation des variables preponderantes est recherchee C’est pourquoi une methodologie combinant des techniques d’AS avec la methode de CS a ete developpee En reduisant le modele aux seules variables predominantes grâce a une premiere etude faisant intervenir les methodes d’AS, la CS peut ensuite retrouver toute son efficacite avec une grande precision Ce processus global a ete valide face a la methode de Monte Carlo sur differentes problematiques mettant en jeu le RT soumis a des aleas de natures variees