{"id":5125,"date":"2025-12-16T17:37:31","date_gmt":"2025-12-16T09:37:31","guid":{"rendered":"https:\/\/www.tfngj.com\/?p=5125"},"modified":"2025-12-17T10:48:05","modified_gmt":"2025-12-17T02:48:05","slug":"principles-of-spectrum-analyzers-and-analysis-of-fft-technology","status":"publish","type":"post","link":"https:\/\/www.tfngj.com\/fr\/principles-of-spectrum-analyzers-and-analysis-of-fft-technology\/","title":{"rendered":"Principes des analyseurs de spectre et analyse de la technologie FFT"},"content":{"rendered":"<p>Dans les domaines des communications sans fil, de l'ing\u00e9nierie audio et de la recherche et du d\u00e9veloppement \u00e9lectroniques, l'analyseur de spectre sert d\u201c\u201dyeux\" aux ing\u00e9nieurs pour percevoir la v\u00e9ritable nature des signaux. Il transforme des formes d'onde complexes dans le domaine temporel en composantes spectrales clairement visibles dans le domaine fr\u00e9quentiel. Aujourd'hui, du point de vue d'un ing\u00e9nieur en recherche et d\u00e9veloppement, je vais me plonger dans les principes de fonctionnement fondamentaux des analyseurs de spectre et me concentrer sur l'analyse de la mise en \u0153uvre et de l'optimisation de l'\u00e2me des instruments modernes - la technologie de la transform\u00e9e de Fourier rapide (Fast Fourier Transform).<\/p>\n\n\n<h2 class=\"wp-block-heading has-4-x-large-font-size\" id=\"traditional-principles-of-spectrum-analyzers-swept-architecture\">Principes traditionnels des analyseurs de spectre : Architecture \u00e0 balayage<\/h2>\n\n\n\n<p>Pour comprendre les instruments modernes, il faut commencer par leur pr\u00e9d\u00e9cesseur, l'analyseur de spectre \u00e0 balayage traditionnel. Son principe de base s'apparente \u00e0 un filtre \u00e0 bande \u00e9troite accordable qui balaie lentement l'ensemble de la gamme de fr\u00e9quences.<\/p>\n\n\n\n<p>R\u00e9ception superh\u00e9t\u00e9rodyne : La base de la conversion du signal vers le bas<\/p>\n\n\n\n<p>L'instrument m\u00e9lange d'abord le signal d'entr\u00e9e avec un signal d'oscillateur local (LO). La formule cl\u00e9 est la suivante :<\/p>\n\n\n\n<p>f_IF = |f_IN - f_LO|<\/p>\n\n\n\n<p>En balayant l'OL, les signaux d'entr\u00e9e de diff\u00e9rentes fr\u00e9quences sont convertis s\u00e9quentiellement en une fr\u00e9quence interm\u00e9diaire (FI) fixe. Ensuite, le signal passe par un filtre \u00e0 largeur de bande de r\u00e9solution (RBW), dont la largeur d\u00e9termine directement la capacit\u00e9 de l'instrument \u00e0 distinguer deux composantes de fr\u00e9quence adjacentes. Enfin, le d\u00e9tecteur d'enveloppe et le filtre vid\u00e9o compl\u00e8tent la mesure de la puissance et le lissage de l'affichage.<\/p>\n\n\n\n<p>Param\u00e8tres cl\u00e9s : RBW, VBW et dur\u00e9e de balayage<\/p>\n\n\n<ul class=\"wp-block-list\" style=\"\">\n<li>Largeur de bande de r\u00e9solution (RBW) : L'une des sp\u00e9cifications les plus critiques de l'instrument. Une largeur de bande de r\u00e9solution plus \u00e9troite offre une r\u00e9solution de fr\u00e9quence plus \u00e9lev\u00e9e, mais augmente \u00e9galement le temps n\u00e9cessaire pour balayer toute la gamme de fr\u00e9quences (dur\u00e9e de balayage). La relation entre ces param\u00e8tres est limit\u00e9e par : Dur\u00e9e de balayage \u2248 Port\u00e9e \/ (RBW)\u00b2. Il s'agit d'un compromis classique en ing\u00e9nierie.<\/li>\n\n\n\n<li>Bande passante vid\u00e9o (VBW) : Utilis\u00e9e pour lisser la trace d'affichage et r\u00e9duire les fluctuations de bruit. Cependant, un lissage excessif peut masquer les v\u00e9ritables d\u00e9tails du signal.<\/li>\n<\/ul>\n\n\n<h2 class=\"wp-block-heading has-4-x-large-font-size\" id=\"the-core-of-modern-spectrum-analyzers-principles-of-fft-analyzers\">Le c\u0153ur des analyseurs de spectre modernes : Principes des analyseurs FFT<\/h2>\n\n\n\n<p>Avec le bond en avant de la technologie du traitement num\u00e9rique des signaux (DSP), les analyseurs de spectre bas\u00e9s sur la technologie FFT sont devenus monnaie courante. Ils modifient fondamentalement la mise en \u0153uvre de l'analyse de spectre.<\/p>\n\n\n\n<p>De la transform\u00e9e de Fourier \u00e0 la FFT : Mise en \u0153uvre technique de la th\u00e9orie<\/p>\n\n\n\n<p>La FFT est un algorithme efficace pour la transform\u00e9e de Fourier discr\u00e8te (DFT). La TFD convertit N points d'\u00e9chantillonnage dans le domaine temporel en N points complexes dans le domaine fr\u00e9quentiel. La formule est la suivante :<\/p>\n\n\n\n<p>X(k) = \u03a3 [x(n) e^(-j2\u03c0kn\/N)], o\u00f9 n = 0 \u00e0 N-1<\/p>\n\n\n\n<p>La complexit\u00e9 de calcul de la TFD directe est de O(N\u00b2), tandis que l'algorithme de la FFT (tel que l'algorithme radix-2 de Cooley-Tukey) la r\u00e9duit \u00e0 O(N log\u2082 N). Cela signifie que pour 4096 points de donn\u00e9es, la FFT est des centaines de fois plus rapide que la DFT directe, ce qui rend possible l'analyse du spectre en temps r\u00e9el.<\/p>\n\n\n\n<p>Processus de mise en \u0153uvre de la FFT dans les analyseurs de spectre<\/p>\n\n\n<ul class=\"wp-block-list\" style=\"\">\n<li>Filtrage anti-repliement et \u00e9chantillonnage ADC : Le signal d'entr\u00e9e passe d'abord par un filtre passe-bas anti-repliement pour garantir la conformit\u00e9 avec le th\u00e9or\u00e8me d'\u00e9chantillonnage de Nyquist (f_s &gt; 2 f_max). Il est ensuite num\u00e9ris\u00e9 par un CAN \u00e0 grande vitesse.<\/li>\n\n\n\n<li>Fen\u00eatrage : Une fonction de fen\u00eatre (par exemple, Hanning, Flat Top) est appliqu\u00e9e au bloc de donn\u00e9es tronqu\u00e9 dans le domaine temporel pour supprimer les fuites spectrales. Le choix de la fonction de fen\u00eatre est crucial pour l'exp\u00e9rience technique : la fen\u00eatre de Hanning offre une haute r\u00e9solution de fr\u00e9quence, tandis que la fen\u00eatre Flat Top offre une meilleure pr\u00e9cision d'amplitude.<\/li>\n\n\n\n<li>Calcul de la FFT et g\u00e9n\u00e9ration d'un spectre d'amplitude : Effectuer une FFT sur les donn\u00e9es fen\u00eatr\u00e9es et calculer l'amplitude de chaque composante de fr\u00e9quence (typiquement 20log10|X(k)|), ce qui permet d'obtenir un spectre lin\u00e9aire ou logarithmique.<\/li>\n<\/ul>\n\n\n<h2 class=\"wp-block-heading has-4-x-large-font-size\" id=\"engineering-tradeoffs-between-fft-technology-and-traditional-sweeping\">Compromis d'ing\u00e9nierie entre la technologie FFT et le balayage traditionnel<\/h2>\n\n\n\n<p>Avantages et sc\u00e9narios d'application des analyseurs FFT<\/p>\n\n\n<ul class=\"wp-block-list\" style=\"\">\n<li>Vitesse extr\u00eamement rapide : Pour une plage fixe, la FFT peut capturer la totalit\u00e9 de la bande de fr\u00e9quences presque en temps r\u00e9el, ce qui la rend id\u00e9ale pour l'analyse des signaux transitoires et des signaux en rafale.<\/li>\n\n\n\n<li>Informations de phase de haute pr\u00e9cision : La FFT produit directement des r\u00e9sultats complexes, en pr\u00e9servant les informations de phase du signal pour une analyse vectorielle ult\u00e9rieure.<\/li>\n\n\n\n<li>Incertitude de mesure plus faible : Pour l'analyse en bande \u00e9troite, il \u00e9vite l'influence du bruit de phase de l'OL pr\u00e9sent dans les analyseurs \u00e0 balayage.<\/li>\n<\/ul>\n\n\n\n<p>Limites inh\u00e9rentes \u00e0 la FFT et strat\u00e9gies d'att\u00e9nuation<\/p>\n\n\n<ul class=\"wp-block-list\" style=\"\">\n<li>Conflit entre la gamme de fr\u00e9quences et la gamme dynamique : Limit\u00e9e par la fr\u00e9quence d'\u00e9chantillonnage de l'ADC, la bande passante instantan\u00e9e d'un analyseur FFT \u00e0 un seul ADC est restreinte. Les ing\u00e9nieurs utilisent la technologie de conversion num\u00e9rique descendante (DDC), en convertissant d'abord les signaux haute fr\u00e9quence dans la bande passante de l'ADC via un m\u00e9lange analogique avant d'effectuer l'analyse FFT.<\/li>\n\n\n\n<li>Effet de cl\u00f4ture et r\u00e9solution de fr\u00e9quence : La FFT produit des points de fr\u00e9quence discrets, avec une r\u00e9solution de fr\u00e9quence \u0394f = f_s \/ N. Pour mesurer avec pr\u00e9cision des signaux \u00e0 p\u00e9riode non enti\u00e8re, des algorithmes d'interpolation ou l'augmentation du nombre de points FFT (N) sont couramment utilis\u00e9s.<\/li>\n\n\n\n<li>Plage dynamique limit\u00e9e par le nombre de bits du CAN : Les instruments \u00e0 hautes performances utilisent des CAN de 16 bits ou plus, combin\u00e9s \u00e0 un contr\u00f4le num\u00e9rique du gain pour \u00e9tendre la plage dynamique.<\/li>\n<\/ul>\n\n\n<h2 class=\"wp-block-heading has-4-x-large-font-size\" id=\"how-to-choose-and-optimize\">Comment choisir et optimiser\uff1f<\/h2>\n\n\n\n<p>Choix du mode d'analyse en fonction des exigences du test<\/p>\n\n\n<ul class=\"wp-block-list\" style=\"\">\n<li>Le mode balay\u00e9 reste utile pour l'analyse des signaux continus \u00e0 l'\u00e9tat stable ou lorsque des port\u00e9es extr\u00eamement larges sont n\u00e9cessaires.<\/li>\n\n\n\n<li>Le mode FFT est essentiel pour l'analyse des signaux de saut de fr\u00e9quence, des interf\u00e9rences transitoires ou lorsque des informations sur la phase sont n\u00e9cessaires.<\/li>\n\n\n\n<li>Les analyseurs de spectre modernes haut de gamme utilisent g\u00e9n\u00e9ralement une architecture hybride, combinant la large gamme de balayage avec l'avantage de la vitesse de la FFT, commut\u00e9e intelligemment par des processeurs internes.<\/li>\n<\/ul>\n\n\n\n<p>L'art de la configuration des param\u00e8tres cl\u00e9s<\/p>\n\n\n<ul class=\"wp-block-list\" style=\"\">\n<li>D\u00e9finissez un taux d'\u00e9chantillonnage appropri\u00e9 (f_s) : Veillez \u00e0 ce qu'elle soit sup\u00e9rieure \u00e0 deux fois la fr\u00e9quence la plus \u00e9lev\u00e9e du signal, avec une certaine marge.<\/li>\n\n\n\n<li>Comprendre l'importance des points FFT (N) : Un plus grand nombre de points N permet d'obtenir une r\u00e9solution de fr\u00e9quence plus fine (\u0394f), mais augmente le temps de calcul. Il est n\u00e9cessaire de trouver un \u00e9quilibre entre la r\u00e9solution et les performances en temps r\u00e9el.<\/li>\n\n\n\n<li>Choisir correctement la fonction de fen\u00eatre : Utilisez la fen\u00eatre de Hanning pour une analyse g\u00e9n\u00e9rale ; envisagez la fen\u00eatre Flat Top pour une mesure pr\u00e9cise de l'amplitude ; utilisez la fen\u00eatre Rectangulaire pour l'analyse de deux signaux tr\u00e8s \u00e9loign\u00e9s l'un de l'autre.<\/li>\n<\/ul>\n\n\n<h2 class=\"wp-block-heading has-4-x-large-font-size\" id=\"conclusion\">Conclusion<\/h2>\n\n\n\n<p>Du balayage analogique \u00e0 la FFT num\u00e9rique, l'\u00e9volution des principes de l'analyseur de spectre est un microcosme du d\u00e9veloppement de la technologie de mesure \u00e9lectronique. En tant qu'ing\u00e9nieur, une compr\u00e9hension approfondie des principes de fonctionnement des analyseurs de spectre et des d\u00e9tails de mise en \u0153uvre de la technologie FFT permet non seulement un fonctionnement plus pr\u00e9cis de l'instrument, mais aussi de voir au-del\u00e0 de l\u201c\u201dapparence\" du spectre, jusqu'\u00e0 l'essence des signaux et des syst\u00e8mes. La ma\u00eetrise de ces principes vous permet de g\u00e9rer facilement les probl\u00e8mes d'interf\u00e9rences \u00e9lectromagn\u00e9tiques ou l'analyse de signaux de communication complexes, et d'\u00e9mettre les jugements et les conceptions les plus professionnels. Cela incarne la valeur de l'exp\u00e9rience et de l'expertise en ing\u00e9nierie.<\/p>","protected":false},"excerpt":{"rendered":"<p>In the fields of wireless communications, audio engineering, and electronic research and development, the spectrum analyzer serves as the &#8220;eyes&#8221; for engineers to perceive the true nature of signals. It transforms complex waveforms in the time domain into clearly visible spectral components in the frequency domain. Today, from the perspective of a research and development [&hellip;]<\/p>","protected":false},"author":1,"featured_media":5126,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7],"tags":[],"class_list":["post-5125","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tfn-blog"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Principles of Spectrum Analyzers and Analysis of FFT Technology<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.tfngj.com\/fr\/principles-of-spectrum-analyzers-and-analysis-of-fft-technology\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Principles of Spectrum Analyzers and Analysis of FFT Technology\" \/>\n<meta property=\"og:description\" content=\"In the fields of wireless communications, audio engineering, and electronic research and development, the spectrum analyzer serves as the &#8220;eyes&#8221; for engineers to perceive the true nature of signals. 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