{"id":167,"date":"2010-11-25T09:50:40","date_gmt":"2010-11-25T08:50:40","guid":{"rendered":"https:\/\/samovar2022.int-evry.fr\/index.php\/2010\/11\/25\/soutenance-these-abdelkader-oukaci\/"},"modified":"2020-09-04T18:47:17","modified_gmt":"2020-09-04T16:47:17","slug":"soutenance-these-abdelkader-oukaci","status":"publish","type":"post","link":"https:\/\/samovar.telecom-sudparis.eu\/index.php\/2010\/11\/25\/soutenance-these-abdelkader-oukaci\/","title":{"rendered":"SOUTENANCE : Th\u00e8se Abdelkader OUKACI"},"content":{"rendered":"

mardi 30 novembre 2010
\n\u00ab\u00a0Beamforming et d\u00e9tection pour signaux non circulaires et\/ou non gaussiens (Algorithmes et performances)<\/strong>\u00ab\u00a0.<\/p>\n

La soutenance aura lieu Mardi 30 Novembre \u00e0 14h30 dans l’amphi OPALE sur le campus de T\u00e9l\u00e9com ParisTech (ex ENST) sis au 46 rue Barrault
\n75013 Paris (Metro Corvisart, ligne 6)<\/p>\n

Elle sera suivie d’un pot en salle E800-1.<\/p>\n

Le jury sera compos\u00e9 de :<\/strong><\/p>\n

– Rapporteur Pierre COMON, Professeur Universit\u00e9 de Nice Antipolis
\n– Rapporteur Pascal LARZABAL, Professeur ENS Cachan
\n– Examinateur Michel BRONIATOWSKI, Professeur Universit\u00e9 Paris VI
\n– Examinateur Philippe FORSTER, Professeur ENS Cachan
\n– Examinateur Yide WANG, Professeur Polytech\u2019Nantes
\n– Co-directeur Pascal CHEVALIER, Professeur CNAM \/ Expert THALES Communication
\n– Directeur Jean Pierre DELMAS, Professeur Telecom SudParis<\/p>\n

R\u00e9sum\u00e9:<\/strong><\/p>\n

Cette th\u00e8se est consacr\u00e9e \u00e0 l\u2019exploitation des propri\u00e9t\u00e9s de non circularit\u00e9 et de non gaussianit\u00e9 des signaux en traitement d\u2019antennes.
\nDans une premi\u00e8re partie de cette th\u00e8se, nous nous int\u00e9ressons au contexte de la formation de voies (beamforming) pour la r\u00e9ception d\u2019un
\nsignal utile inconnu, dont le vecteur directionnel est connu,
\ncorrompu par un bruit potentiellement non circulaire et\/ou non gaussien. Dans des \u00e9tudes r\u00e9centes, un beamformer MVDR (Minimum Variance Distortionless Response) lin\u00e9aire au sens large WL (Widely
\nLinear) exploitant la non circularit\u00e9 au second ordre (SO) des interf\u00e9rences a \u00e9t\u00e9 introduit et analys\u00e9. Cependant, ce beamformer demeure sous optimal pour la r\u00e9ception d\u2019un signal utile non circulaire au SO, du moment o\u00f9 il n\u2019exploite pas la non circularit\u00e9 de ce dernier. C\u2019est ainsi, que notre contribution a port\u00e9 principalement sur l\u2019introduction, l\u2019\u00e9tude de performances et la mise en oeuvre d\u2019un beamformer MVDR WL. Ce dernier, bas\u00e9 sur une d\u00e9composition orthogonale originale du signal utile introduisant une contrainte suppl\u00e9mentaire, prend en consid\u00e9ration la non circularit\u00e9 du signal utile et celle des interf\u00e9rences. L\u2019\u00e9tude des performances de ce beamformer a montr\u00e9 que ce dernier am\u00e9liore toujours les performances en pr\u00e9sence de signaux non circulaires. Dans le m\u00eame contexte et pour la r\u00e9ception de signaux non gaussiens, nous avons introduit et \u00e9tudi\u00e9 un beamformer MVDR non lin\u00e9aire de Volterra. Ce beamformer dont les contraintes s\u2019adaptent \u00e0 la non circularit\u00e9 des brouilleurs, a \u00e9t\u00e9 \u00e9tudi\u00e9 \u00e0 l\u2019ordre trois sous sa forme \u00e9quivalente GSC. Cette structure, dite compl\u00e8te, prend en compte conjointement des propri\u00e9t\u00e9s de non circularit\u00e9 et de non gaussianit\u00e9 des brouilleurs. L\u2019analyse des performances en gains en SINR de ce r\u00e9cepteur est donn\u00e9e pour la r\u00e9ception d\u2019un signal r\u00e9el corrompu par des brouilleurs non gaussiens et non circulaires d\u2019ordre deux et quatre. Cette analyse a montr\u00e9 que la prise en consid\u00e9ration de ces propri\u00e9t\u00e9s am\u00e9liore toujours les performances.<\/p>\n

Dans une deuxi\u00e8me partie nous nous int\u00e9ressons au contexte de d\u00e9tection selon deux volets :<\/p>\n

Le premier volet consiste en la d\u00e9tection d\u2019un signal utile r\u00e9el connu de param\u00e8tres inconnus, noy\u00e9 dans un bruit total potentiellement non circulaire au SO et de matrice de covariance inconnue. Ainsi, suivant une approche bas\u00e9e sur le test de rapport de vraisemblance g\u00e9n\u00e9ralis\u00e9 GLRT (Generalized Likelihood Ratio Test), de nouveaux r\u00e9cepteurs pour la d\u00e9tection d\u2019un signal r\u00e9el connu avec diff\u00e9rents ensembles de param\u00e8tres inconnus ont \u00e9t\u00e9 r\u00e9cemment introduits. N\u00e9anmoins, les performances de ces r\u00e9cepteurs, n\u2019ont \u00e9t\u00e9 que partiellement \u00e9tudi\u00e9es.
\nNotre contribution a port\u00e9 sur l\u2019\u00e9tude des distributions exactes et asymptotiques des statistiques associ\u00e9es au LRT et au GLRT sous H0 et H1. Cette \u00e9tude a permis de donner les expressions th\u00e9oriques exactes des probabilit\u00e9s de d\u00e9tection et de fausse alarme des r\u00e9cepteurs LRT, et celles asymptotiques pour certains r\u00e9cepteurs GLRT. Nous avons aussi compl\u00e9t\u00e9 cette analyse par des simulations Monte-Carlo en courbes ROC (Receiver Operating Characterisics) pour l\u2019ensemble des d\u00e9tecteurs GLRT.<\/p>\n

Le deuxi\u00e8me volet, consiste en la d\u00e9tection de non circularit\u00e9 au SO de signaux al\u00e9atoires mono et multidimensionnels complexes. Nous avons donn\u00e9 la distribution asymptotique du GLR de non circularit\u00e9 sous H0 et H1 d\u00e9riv\u00e9 sous l\u2019hypoth\u00e8se de distribution gaussienne mais utilis\u00e9e sous une distribution arbitraire non n\u00e9cessairement gaussienne des donn\u00e9es. Ces donn\u00e9es consid\u00e9r\u00e9es sont ind\u00e9pendantes, mais non n\u00e9cessairement identiquement distribu\u00e9es, ce qui permet de traiter des situations pratiques o\u00f9 les donn\u00e9es non circulaires sont perturb\u00e9es par un r\u00e9sidu de fr\u00e9quence et un bruit additif gaussien circulaire.
\nCette analyse a \u00e9t\u00e9 aussi compl\u00e9t\u00e9e par des courbes ROC.<\/p>\n

Abstract:<\/strong><\/p>\n

This thesis is devoted to the study of exploiting the properties of non-circularity and non-Gaussianity of signals in array processing.
\nIn the first part of this thesis, we focus on beamforming technics in the context of the reception of an unknown signal, whose steering vector is known, corrupted by potentially non-circular and\/or non-Gaussian noise. In recent studies, a widely linear minimum variance distortionless response beamformer (WL MVDR) exploiting the second order (SO) non-circularity of interference was introduced and analyzed. However, this beamformer remains suboptimal for the reception of a non-circular useful signal, since it does not exploit the non-circularity of this latter. Thus, our contribution has focused on the introduction, the performances analysis and the implementation of a WL MVDR Beamformer. This latter, based on an original orthogonal decomposition of the useful signal, take into account the SO non-circularity of both useful signal and interferences. The new performances analysis of this new beamformer has shown that it always improves the performance of the well known Capon beamformer and the WL MVDR beamformer introduced recently, this in the presence of non-circular signals. In the same context and for receiving non-Gaussian signals, we introduced and studied a nonlinear MVDR Beamformer based on comlexe Volterra filters. This Beamformer, which adapt the constraints to the non circularity of jammers, has been studied in the third order by its equivalent GSC form. The performance analysis of this beamformer are shown in term of SINR Gains for the recepetion of non-Gaussian and SO (until to fourth order) non-circular. It is shown that taking into account of these properties always improves performance. In the second part, we focus on two parts of detection :<\/p>\n

The first part consists of the detection a known signal, with unknown parameters, corrupted by a total noise potentially SO noncircular with unknown covariance matrix. Thus, following Generalized Likelihood Ratio Test approach, new receivers for the detection a real known signal with different sets of unknown parameters have been recently introduced.
\nNevertheless, the performances analysis of these receptors have only been partially studied. Our contribution has focused on the study of exact and asymptotic distributions of statistics associated with the LRT and GLRT under H0 and H1. This study has given theoretical expressions of probabilities of correct detection and false alarm. We also supplemented this analysis with Monte Carlo simulations and given receiver operating characterisics ROC curves. <\/p>\n

In the second part, we consider the problem of testing impropriety (i.e., second-order
\nnoncircularity) of a complex valued random variable based on the generalized likelihood ratio test (GLRT) for Gaussian distributions.
\nAsymptotic (w.r.t. the data length) distributions of the GLR are given under the hypothesis that data are proper or improper, and under the true, not necessarily Gaussian distribution of the data.
\nThe considered data are independent but not necessarily identically distributed : assumption which has never been considered until now.
\nThis enables us to deal with the practical important situations of noncircular data disturbed by residual frequency offsets and additive circular noise. The receiver operating characteristic (ROC) of this test is derived as byproduct, an issue previously overlooked. Finally illustrative examples are presented in order to strengthen the obtained theoretical results.<\/p>\n

\n","protected":false},"excerpt":{"rendered":"

mardi 30 novembre 2010 \u00ab\u00a0Beamforming et d\u00e9tection pour signaux non circulaires et\/ou non gaussiens (Algorithmes et performances)\u00ab\u00a0. La soutenance aura lieu Mardi 30 Novembre \u00e0 14h30 dans l’amphi OPALE sur le campus de T\u00e9l\u00e9com ParisTech (ex ENST) sis au 46 rue Barrault 75013 Paris (Metro Corvisart, ligne 6) Elle sera suivie d’un pot en salle […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"ocean_post_layout":"","ocean_both_sidebars_style":"","ocean_both_sidebars_content_width":0,"ocean_both_sidebars_sidebars_width":0,"ocean_sidebar":"","ocean_second_sidebar":"","ocean_disable_margins":"enable","ocean_add_body_class":"","ocean_shortcode_before_top_bar":"","ocean_shortcode_after_top_bar":"","ocean_shortcode_before_header":"","ocean_shortcode_after_header":"","ocean_has_shortcode":"","ocean_shortcode_after_title":"","ocean_shortcode_before_footer_widgets":"","ocean_shortcode_after_footer_widgets":"","ocean_shortcode_before_footer_bottom":"","ocean_shortcode_after_footer_bottom":"","ocean_display_top_bar":"default","ocean_display_header":"default","ocean_header_style":"","ocean_center_header_left_menu":"","ocean_custom_header_template":"","ocean_custom_logo":0,"ocean_custom_retina_logo":0,"ocean_custom_logo_max_width":0,"ocean_custom_logo_tablet_max_width":0,"ocean_custom_logo_mobile_max_width":0,"ocean_custom_logo_max_height":0,"ocean_custom_logo_tablet_max_height":0,"ocean_custom_logo_mobile_max_height":0,"ocean_header_custom_menu":"","ocean_menu_typo_font_family":"","ocean_menu_typo_font_subset":"","ocean_menu_typo_font_size":0,"ocean_menu_typo_font_size_tablet":0,"ocean_menu_typo_font_size_mobile":0,"ocean_menu_typo_font_size_unit":"px","ocean_menu_typo_font_weight":"","ocean_menu_typo_font_weight_tablet":"","ocean_menu_typo_font_weight_mobile":"","ocean_menu_typo_transform":"","ocean_menu_typo_transform_tablet":"","ocean_menu_typo_transform_mobile":"","ocean_menu_typo_line_height":0,"ocean_menu_typo_line_height_tablet":0,"ocean_menu_typo_line_height_mobile":0,"ocean_menu_typo_line_height_unit":"","ocean_menu_typo_spacing":0,"ocean_menu_typo_spacing_tablet":0,"ocean_menu_typo_spacing_mobile":0,"ocean_menu_typo_spacing_unit":"","ocean_menu_link_color":"","ocean_menu_link_color_hover":"","ocean_menu_link_color_active":"","ocean_menu_link_background":"","ocean_menu_link_hover_background":"","ocean_menu_link_active_background":"","ocean_menu_social_links_bg":"","ocean_menu_social_hover_links_bg":"","ocean_menu_social_links_color":"","ocean_menu_social_hover_links_color":"","ocean_disable_title":"default","ocean_disable_heading":"default","ocean_post_title":"","ocean_post_subheading":"","ocean_post_title_style":"","ocean_post_title_background_color":"","ocean_post_title_background":0,"ocean_post_title_bg_image_position":"","ocean_post_title_bg_image_attachment":"","ocean_post_title_bg_image_repeat":"","ocean_post_title_bg_image_size":"","ocean_post_title_height":0,"ocean_post_title_bg_overlay":0.5,"ocean_post_title_bg_overlay_color":"","ocean_disable_breadcrumbs":"default","ocean_breadcrumbs_color":"","ocean_breadcrumbs_separator_color":"","ocean_breadcrumbs_links_color":"","ocean_breadcrumbs_links_hover_color":"","ocean_display_footer_widgets":"default","ocean_display_footer_bottom":"default","ocean_custom_footer_template":"","ocean_post_oembed":"","ocean_post_self_hosted_media":"","ocean_post_video_embed":"","ocean_link_format":"","ocean_link_format_target":"self","ocean_quote_format":"","ocean_quote_format_link":"post","ocean_gallery_link_images":"on","ocean_gallery_id":[],"footnotes":""},"categories":[440],"tags":[],"class_list":["post-167","post","type-post","status-publish","format-standard","hentry","category-theses-2010-fr","entry"],"_links":{"self":[{"href":"https:\/\/samovar.telecom-sudparis.eu\/index.php\/wp-json\/wp\/v2\/posts\/167","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/samovar.telecom-sudparis.eu\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/samovar.telecom-sudparis.eu\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/samovar.telecom-sudparis.eu\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/samovar.telecom-sudparis.eu\/index.php\/wp-json\/wp\/v2\/comments?post=167"}],"version-history":[{"count":1,"href":"https:\/\/samovar.telecom-sudparis.eu\/index.php\/wp-json\/wp\/v2\/posts\/167\/revisions"}],"predecessor-version":[{"id":2055,"href":"https:\/\/samovar.telecom-sudparis.eu\/index.php\/wp-json\/wp\/v2\/posts\/167\/revisions\/2055"}],"wp:attachment":[{"href":"https:\/\/samovar.telecom-sudparis.eu\/index.php\/wp-json\/wp\/v2\/media?parent=167"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/samovar.telecom-sudparis.eu\/index.php\/wp-json\/wp\/v2\/categories?post=167"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/samovar.telecom-sudparis.eu\/index.php\/wp-json\/wp\/v2\/tags?post=167"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}