Master 2014 2015
Stages de la spécialité SAR
Advanced Estimation Methods For Radio-Astronomy : Calibration & Inverse problems

Site :SATIE laboratory of ENS Cachan
Lieu :Laboratoire d’accueil SATIE de l'ENS Cachan (pour le stage sur la radio astronomie, adresse 1 Avenue du Président Wilson, 94230 Cachan)
Encadrant : Prof. P. Larzabal (, Dr./HDR R. Boyer ( and Dr. M. N. El Korso (
Dates :Mars-Avril à Juillet-Aout
Rémunération :479,95 euros)
Mots-clés : Parcours ATIAM : Traitement du signal


Conditions : o An outstanding and highly motivated candidate is solicited in the SATIE laboratory of ENS Cachan and signals and system laboratory (L2S) of Paris XI University-SUPELEC for a 5 to 6 months internship. o Students at the M.Sc., M. Eng., Master (or equivalent) level with background in signal processing, probability, statistics, or information theory are encouraged to apply. Good mathematical background is required. Above all, the applicants must be motivated to learn quickly and work effectively on challenging research problems.

Application process : Please send your CV, transcripts of grades with qualifications and pertinent information, as soon as possible, to Prof. P. Larzabal (, Dr./HDR R. Boyer ( and Dr. M. N. El Korso (

Short description of the internship : This internship concerns the calibration and imaging in the radio-astronomy context. Future astronomical instruments will be constituted of a largely distributed sensor arrays with a hierarchy of phased array elements. In order to provide meaningful images for such arrays, accurate calibration is of critical importance. Calibration must solve the unknown antenna gains and phases as well as the unknown atmospheric and ionospheric disturbances. Furthermore, future telescopes will have a large number of elements and a large field of view. Consequently, such parameters are strongly direction-dependent, resulting in a large number of unknown nuisance parameters. All this makes calibration a daunting parameter estimation task for which the existing methods are ineffective. In this internship, we will overcome this drawback by designing advanced statistical robust algorithms based on probabilistic modeling which can marginalize the unknown nuisance parameter. Finally, the specificity of the above problem requires a performance analysis of the proposed calibration schemes in the context of large data. This internship is a part of the ANR MAGELLAN and the mastodons/display CNRS projects (with collaboration with LTCI TelecomParisTech and Lagrance Nice-Université laboratories). Depending on the motivation of the candidate, a Ph.D. thesis pursuit can be envisaged.


References : [1] S. J. Wijnholds, S. Tol, R. Nijboer, and A. V. D. Veen, “Calibration challenges for future radio telescopes,” IEEE Signal Processing Mag., vol. 27, pp. 30-42, Jan. 2010. [2] S. Kazemi and S. Yatawatta, “Robust radio interferometric calibration using the t-distribution,” Monthly Notices of the Royal Astronomical Society, vol. 435, no. 1, pp. 597–605, Oct. 2013. [3] D. N. Tran, A. Renaux, R. Boyer, S. Marcos and P. Larzabal “Performance bounds for the pulse phase estimation of X-ray pulsar”, In IEEE Trans. on Aerospace and Electronic Systems, accepted for publication, 2014. [4] J. Bosse, A. Ferreol and P. Larzabal “A spatio-temporal array processing for passive localization of radio transmitters”, IEEE Trans. on signal processing, accepted for publication, 2014. [5] X. Zhang, M. N. El Korso, and M. Pesavento, "MIMO Radar Performance Analysis under K-distributed Clutter’’, ICASSP-2014, May 2014, Florence, Italy. [6] M. Haardt, M. Pesavento, F. Röemer and M. N. El Korso, "Subspace Methods and Exploitation of Special Array Structures", Electronic Reference in Signal Processing : Array and Statistical Signal Processing, vol. 3, pp. 651-717, Academic Press Library in Signal Processing, Elsevier Ltd., 2014, Chapter 2.15, ISBN 978-0-12-411597-2. [7] A. Leshem and A. V. D. Veen, “Radio astronomical imaging in the presence of strong radio interference,” IEEE Trans. Inform. Theory, vol. 46, pp. 1730-1747, Aug. 2000. [8] S. J. Wijnholds and A. V. D. Veen, “Multisource self-calibration for sensor arrays”, IEEE Trans. Signal Processing, vol. 57, pp. 3512-3522, Sep. 2009.