268 citations · 1.4k across the 80 of their papers we have counts for
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Grid Hopping: Accelerating Direct Estimation Algorithms for Multistatic FMCW Radar
Gilles Monnoyer, Thomas Feuillen, Maxime Drouguet +2
This paper presents a novel signal processing technique, coined grid hopping, as well as an active multistatic Frequency-Modulated Continuous Wave (FMCW) radar system designed to e…
Signal processing after quadratic random sketching with optical units
Rémi Delogne, Vincent Schellekens, Laurent Daudet +1
Random data sketching (or projection) is now a classical technique enabling, for instance, approximate numerical linear algebra and machine learning algorithms with reduced computa…
Interferometric single-pixel imaging with a multicore fiber
Olivier Leblanc, Matthias Hofer, Siddharth Sivankutty +2
Lensless illumination single-pixel imaging with a multicore fiber (MCF) is a computational imaging technique that enables potential endoscopic observations of biological samples at…
Learning to Reconstruct Signals From Binary Measurements
Julián Tachella, Laurent Jacques
Recent advances in unsupervised learning have highlighted the possibility of learning to reconstruct signals from noisy and incomplete linear measurements alone. These methods play…
Min-Path-Tracing: A Diffraction Aware Alternative to Image Method in Ray Tracing
Jérome Eertmans, Claude Oestges, Laurent Jacques
For more than twenty years, Ray Tracing methods have continued to improve on both accuracy and computational time aspects. However, most state-of-the-art image-based ray tracers st…
Signal processing with optical quadratic random sketches
Rémi Delogne, Vincent Schellekens, Laurent Daudet +1
Random data sketching (or projection) is now a classical technique enabling, for instance, approximate numerical linear algebra and machine learning algorithms with reduced computa…
ROP inception: signal estimation with quadratic random sketching
Rémi Delogne, Vincent Schellekens, Laurent Jacques
Rank-one projections (ROP) of matrices and quadratic random sketching of signals support several data processing and machine learning methods, as well as recent imaging application…
Sparse Factorization-based Detection of Off-the-Grid Moving targets using FMCW radars
Gilles Monnoyer de Galland, Thomas Feuillen, Luc Vandendorpe +1
In this paper, we investigate the application of continuous sparse signal reconstruction algorithms for the estimation of the ranges and speeds of multiple moving targets using an…
Going Below and Beyond, Off-the-Grid Velocity Estimation from 1-bit Radar Measurements
Gilles Monnoyer de Galland, Thomas Feuillen, Luc Vandendorpe +1
In this paper we propose to bridge the gap between using extremely low resolution 1-bit measurements and estimating targets' parameters, such as their velocities, that exist in a c…
One Bit to Rule Them All : Binarizing the Reconstruction in 1-bit Compressive Sensing
Thomas Feuillen, Mike Davies, Luc Vandendorpe +1
This work focuses on the reconstruction of sparse signals from their 1-bit measurements. The context is the one of 1-bit compressive sensing where the measurements amount to quanti…
Factorization over interpolation: A fast continuous orthogonal matching pursuit
Gilles Monnoyer de Galland, Luc Vandendorpe, Laurent Jacques
We propose a fast greedy algorithm to compute sparse representations of signals from continuous dictionaries that are factorizable, i.e., with atoms that can be separated as a prod…
Breaking the waves: asymmetric random periodic features for low-bitrate kernel machines
Vincent Schellekens, Laurent Jacques
Many signal processing and machine learning applications are built from evaluating a kernel on pairs of signals, e.g. to assess the similarity of an incoming query to a database of…
Sparsity-Driven Moving Target Detection in Distributed Multistatic FMCW Radars
Gilles Monnoyer de Galland, Thomas Feuillen, Laurent Jacques +1
We investigate the problem of sparse target detection from widely distributed multistatic \textit{Frequency Modulated Continuous Wave} (FMCW) radar systems (using chirp modulation)…
(l1,l2)-RIP and Projected Back-Projection Reconstruction for Phase-Only Measurements
Thomas Feuillen, Mike E. Davies, Luc Vandendorpe +1
This letter analyzes the performances of a simple reconstruction method, namely the Projected Back-Projection (PBP), for estimating the direction of a sparse signal from its phase-…
Identifiability Conditions for Multi-channel Blind Deconvolution with Short Filters
Antoine Paris, Laurent Jacques
This work considers the multi-channel blind deconvolution problem under the assumption that the channels are short. First, we investigate the ill-posedness issues inherent to blind…
An extreme bit-rate reduction scheme for 2D radar localization
Thomas Feuillen, Luc Vandendorpe, Laurent Jacques
In this paper, we further expand on the work in [1] that focused on the localization of targets in a 2D space using 1-bit dithered measurements coming from a 2 receiving antennae r…
Quantity over Quality: Dithered Quantization for Compressive Radar Systems
Thomas Feuillen, Chunlei Xu, Jérôme Louveaux +2
In this paper, we investigate a trade-off between the number of radar observations (or measurements) and their resolution in the context of radar range estimation. To this end, we…
1-bit Localization Scheme for Radar using Dithered Quantized Compressed Sensing
Thomas Feuillen, Chunlei Xu, Luc Vandendorpe +1
We present a novel scheme allowing for 2D target localization using highly quantized 1-bit measurements from a Frequency Modulated Continuous Wave (FMCW) radar with two receiving a…