Historical overview and current research on noise radar
Notice bibliographique
Résumé
The concept of noise radar with coherent reception of radar returns starts its history as early as in 1950s. The first papers on range-measuring radar based upon noise signals were published by Richard Bourret in 1957 who applied CW noise waveform along with its correlation reception and by B.M. Horton in 1959 who also used CW noise signal, but being used for frequency modulation along with so called anticorrelation method for signal processing. Horton recognized that one way to eliminate range and Doppler ambiguities was to use random noise as the modulating function and perform range determination by cross-correlating the return signal with a time-delayed replica of the transmit waveform. In his seminal paper in the May 1959 issue of the Proceedings of the IRE entitled “Noise-modulated distance measuring systems” on pages 821–828, he derived the fundamental concepts and proposed several implementations. Further papers on that subject were published in the period of 1960s and 1970s which may be characterized as a period of initial studies and performance analyses by a handful of researchers. Relatively little development took place in 1980s, though in that new methods for efficient generation of chaotic signals in millimeter wave electron devices have been suggested and autodyne effect in chaotic oscillators has been revealed in 1987 in Ukraine. Advance system development and demonstration by several groups all over the world were done in 1990s and 2000s: Several research groups around the world have developed new applications for noise radar and made significant contributions towards detection, surveillance, tracking, and imaging of targets. Noise radars have the unique property that allows them to achieve high resolution in both range and Doppler which can be independently controlled by varying the bandwidth and integration time respectively. Noise radars satisfy important requirements for military systems, such as low probability of intercept (LPI) and low probability of detection (LPD), owing to the featureless characteristics of its waveform. They also have excellent resistance to jamming and interference. Another advantage of noise radars is their ability to efficiently share the frequency spectrum, thereby allowing a number of noise radars to operate over the same frequency band with minimal cross-interference. This spectrally parsimonious feature can be used to integrate several noise radars to a network centric platform. Much of the early development was hampered by the lack of suitable critical components for fully operational use. However, in recent years, noise radar systems are finding increasing applications in several conventional as well as new areas (e.g., through-wall imaging, multi-static sensing, radar networking) owing to significant advances in RF, digital, and signal processing technologies. Figure 1. shows coarse grain classification of signal processing methods applicable and being used in Noise Radar developed by different research groups. The most popular of them is correlation reception of noise radar returns which has been applied in the very first experiments in Noise Radar. At the same time, so called spectral interferometry method, or its simplified option, double spectral processing, and autodyne (self-mixing) effect may be also applied in case of short range operation. Double spectral processing was pioneered by L Arkhipov in USSR (1961) and independently by J.L. Poirier in US (1968). Nowadays, intensive research in noise radar is ongoing in the U.S., Ukraine, U.K., France, Canada, Germany, Italy, Russia, Poland, Sweden, Norway, China, South Korea and India. Researchers are making many attempts to investigate and experimentally approve capabilities of Noise Radar Technology via design of major, if not all, types of radars.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,005 | 0,008 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,004 | 0,005 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,016 | 0,014 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».