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Engineering and Technology

D-Index
39
Citations
5318
World Ranking
7778
National Ranking
171

Overview

Olivier Besson is affiliated with the National Higher French Institute of Aeronautics and Space in France. Their research primarily spans the fields of Engineering and Computer Science, with a focus on several specialized subfields.

Besson's main areas of study include Aerospace Engineering and Signal Processing, supplemented by interests in Media Technology, Oceanography, and Statistics and Probability. The central topics in their work involve Radar Systems and Signal Processing, Direction-of-Arrival Estimation Techniques, Remote-Sensing Image Classification, Underwater Acoustics Research, Infrared Target Detection Methodologies, Advanced SAR Imaging Techniques, and Advanced Statistical Methods and Models.

The scientist has contributed extensively to academic journals and conferences. Frequent publication venues include Signal Processing, IEEE Signal Processing Letters, arXiv (Cornell University), IEEE Transactions on Signal Processing, and IEEE Transactions on Geoscience and Remote Sensing.

Selected recent papers authored or co-authored by Olivier Besson are:

  • Rao, Wald, and Gradient Tests for Adaptive Detection of Swerling I Targets, 2023, IEEE Transactions on Signal Processing
  • Adaptive Detection of Gaussian Rank-One Signals Using Adaptively Whitened Data and Rao, Gradient and Durbin Tests, 2023, IEEE Signal Processing Letters

Notably, Besson has also co-authored with other researchers in the field. Frequent co-authors include François Vincent, Éric Chaumette, Benjamin Gigleux, Stefania Matteoli, and Jordi Vilà-Valls.

Collaborative works with François Vincent stand out, with a number of publications featuring Vincent as the primary author on topics related to hyperspectral imaging and GNSS receiver positioning:

  • One-Step Generalized Likelihood Ratio Test for Subpixel Target Detection in Hyperspectral Imaging, 2020, IEEE Transactions on Geoscience and Remote Sensing
  • Doppler-aided positioning in GNSS receivers - A performance analysis, 2020, Signal Processing
  • Generalized likelihood ratio test for modified replacement model in hyperspectral imaging detection, 2020, Signal Processing

Olivier Besson's work frequently addresses statistical testing methods and detection techniques applied to hyperspectral imaging and signal processing, reflecting a detail-oriented approach to advanced analytical and computational challenges in these domains.

Best Publications

  • On parameter estimation of MIMO flat-fading channels with frequency offsets

    O. Besson;P. Stoica

  • Decoupled estimation of DOA and angular spread for a spatially distributed source

    O. Besson;P. Stoica

  • An Improved Parallel Multiple-point Algorithm Using a List Approach

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  • Training sequence design for frequency offset and frequency-selective channel estimation

    P. Stoica;O. Besson

  • Approximate maximum likelihood estimators for array processing in multiplicative noise environments

    O. Besson;F. Vincent;P. Stoica;A.B. Gershman

  • A Bayesian Approach to Adaptive Detection in Nonhomogeneous Environments

    S. Bidon;O. Besson;J.-Y. Tourneret

  • An ABORT-Like Detector With Improved Mismatched Signals Rejection Capabilities

    F. Bandiera;O. Besson;G. Ricci

  • Knowledge-Aided Bayesian Detection in Heterogeneous Environments

    O. Besson;J.-Y. Tourneret;S. Bidon

  • GLRT-Based Direction Detectors in Homogeneous Noise and Subspace Interference

    F. Bandiera;O. Besson;D. Orlando;G. Ricci

  • Steering vector errors and diagonal loading

    François Vincent;Olivier Besson

  • Parameter estimation for random amplitude chirp signals

    O. Besson;M. Ghogho;A. Swami

  • On estimating the frequency of a sinusoid in autoregressive multiplicative noise

    Olivier Besson;Francis Castanié

  • Performance analysis of beamformers using generalized loading of the covariance matrix in the presence of random steering vector errors

    O. Besson;F. Vincent

  • Matched direction detectors and estimators for array processing with subspace steering vector uncertainties

    O. Besson;L.L. Scharf;F. Vincent

  • Knowledge-Aided Covariance Matrix Estimation and Adaptive Detection in Compound-Gaussian Noise

    Francesco Bandiera;Olivier Besson;Giuseppe Ricci

  • Adaptive Detection of a Signal Known Only to Lie on a Line in a Known Subspace, When Primary and Secondary Data are Partially Homogeneous

    O. Besson;L.L. Scharf;S. Kraut

  • On the Fisher Information Matrix for Multivariate Elliptically Contoured Distributions

    Olivier Besson;Yuri I. Abramovich

  • Estimation of directions of arrival of multiple scattered sources

    M. Ghogho;O. Besson;A. Swami

  • Adaptive Detection of Distributed Targets in Compound-Gaussian Noise Without Secondary Data: A Bayesian Approach

    F. Bandiera;O. Besson;G. Ricci

  • Sinusoidal signals with random amplitude: least-squares estimators and their statistical analysis

    O. Besson;P. Stoica

  • The Adaptive Coherence Estimator is the Generalized Likelihood Ratio Test for a Class of Heterogeneous Environments

    S. Bidon;O. Besson;J.-Y. Tourneret

Frequent Co-Authors

Petre Stoica
Petre Stoica Uppsala University
Jean-Yves Tourneret
Jean-Yves Tourneret National Polytechnic Institute of Toulouse
Giuseppe Ricci
Giuseppe Ricci University of Salento
Louis L. Scharf
Louis L. Scharf Colorado State University
Danilo Orlando
Danilo Orlando IEEE Computer Society
Alex B. Gershman
Alex B. Gershman Technical University of Darmstadt
Nicolas Dobigeon
Nicolas Dobigeon National Polytechnic Institute of Toulouse
Fulvio Gini
Fulvio Gini University of Pisa
Hugh Griffiths
Hugh Griffiths University College London
Ananthram Swami
Ananthram Swami United States Army Research Laboratory

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