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Zastosowanie metod CLEAN do detekcji słabych ech radiolokacyjnych na tle silnych zakłóceń biernych

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Warianty tytułu
EN
Application of the CLEAN class methods for detecting weak radar signals in the presence of strong interference signals
Języki publikacji
PL
Abstrakty
PL
W pracy przedstawiono wyniki wieloletnich badań autora nad zastosowaniem metod klasy CLEAN do wykrywania słabych użytecznych sygnałów radiolokacyjnych w obecności silnych niepożądanych sygnałów zakłócających. Cechą szczególną zaproponowanego podejścia jest odstąpienie od koncepcji filtracji dopasowanej, stosowanej obecnie powszechnie w technice radiolokacyjnej do wykrywania obiektów. Zastosowanie filtracji dopasowanej prowadzi bowiem do optymalnej detekcji ech radiolokacyjnych jedynie wówczas, gdy odebrane echa, pochodzące od różnych obiektów, nie nakładają się na siebie. W przypadku występowania wielu nakładających się na siebie ech, czasowe lub częstotliwościowe listki boczne, generowane na wyjściu filtru dopasowanego przez silne wejściowe echa zakłócające, mogą mieć znacznie wyższy poziom mocy, niż słabe echa pochodzące od obiektów użytecznych. W konsekwencji, obiekty o dużej odbiciowości mogą całkowicie zamaskować obiekty o malej odbiciowości, interesujące z punktu widzenia użytkownika radaru. W pracy pokazano, że zastosowanie metod klasy CLEAN, polegających - ogólnie rzecz biorąc - na adekwatnym modelowaniu ech obiektów o dużej odbiciowości i usunięciu modelowanych sygnałów z sygnału odebranego, redukuje w znacznym stopniu efekt maskowania i pozwala na skuteczne wykrywanie słabych ech na tle ech silnych (traktowanych w pracy jako zakłócenia bierne). Skonstruowane w tym celu przez autora modele ech, zarówno użytecznych, jak i zakłócających, były oparte na wnikliwej analizie fizycznej strony zjawiska odbicia fali elektromagnetycznej od różnego rodzaju obiektów radiolokacyjnych oraz analizie warunków propagacji tej fali w różnych sytuacjach środowiskowych. Zaproponowane podejście zilustrowano na przykładzie trzech zagadnień radiolokacyjnych będących w ostatnich latach przedmiotem intensywnych badań autora. Dotyczą one: (1) poprawy jakości obrazów uzyskiwanych w radarach SAR z syntetyczną aperturą, (2) wykrywania i identyfikacji helikopterów na podstawie charakterystycznych składowych echa helikoptera oraz (3) wykrywania słabych ech występujących na tle silnych sygnałów zakłócających przez radary szumowe i pasywne, zarówno m ono statyczne, jak multi statyczne. Wszystkie przedstawione w pracy metody i algorytmy zostały zweryfikowane zarówno w badaniach symulacyjnych z wykorzystaniem sygnałów syntetycznych, jak i w badaniach eksperymentalnych z wykorzystaniem rzeczywistych sygnałów zarejestrowanych za pomocą pracujących urządzeń radiolokacyjnych. Przeprowadzone badania wykazały, że zaproponowane metody umożliwiają znaczną poprawę dynamiki radaru oraz znaczące zwiększenie wiarygodności detekcji słabych ech użytecznych, a tym samym poprawę jakości pracy urządzeń radiolokacyjnych. Większość zaproponowanych w pracy algorytmów, w uproszczonych wersjach zaadaptowanych do wymogów pracy w czasie rzeczywistym, zostało zaimplementowanych i wdrożonych w radarach produkowanych przez krajowy przemysł radiolokacyjny.
EN
This book presents results of long-term research on application of the CLEAN class methods for detecting weak radar signals in the presence of strong interference signals. The uniqueness of the proposed approach lies in departure from the matched filtration generally in use to detect objects in the radar technique nowadays. Application of the matched filtration leads to optimum-detection of the radar echoes only when echoes which are received from different objects do not superimpose on each other. In case of many superimposed echoes, time or frequency side lobes, generated by strong interfering echoes on the matched filter output, can have considerably higher power level than weak echoes received from the objects of interest. Consequently, objects of high echo reflectivity can completely niask objects of Iow echo reflectivity, interesting for the radar's user. The presented results demonstrate that the application of CLEAN class methods - relying, in general, on adequate modeling echoes of high reflectivity objects, and on removal of modeled signals from the signal received - reduces significantly the mask effect. This allows efficient detection of weak signals in the presence of strong signals of the background scene (treated in the research as passive interferences). The echo models, constructed by the author for both functional and interfering signals, are based on a detailed study of physical aspects of the electromagnetic wave reflection from various types of radar objects, and on an analysis of conditions of this wave propagation in diverse environments. The proposed approach is illustrated with examples of three radar issues being subject of the author's intensive research over the recent years. They refer to the following topics: (1) improvement of quality of images received by the synthetic aperture (SAR) radars, (2) detection and identification of helicopters on the basis of their echo characteristics, and (3) detection of weak echoes occurring against a background of strong interfering signals, by noise and passive radars, both monostatic and multistatic. All methods and algorithms presented in this paper were verified by the application of synthetic signal simulation as well as experimental research utilizing real signals registered by radar devices. Research results show that the proposed methods facilitate considerable improvement of the radar dynamics and significant enlargement of reliability of detection of the weak radar signals, thus leading to improvement of radar device quality. Most of the proposed algorithms - after some simplifications required for real-time applications - were implemented and put into practice in the systems produced by the national radar industry.
Rocznik
Tom
Strony
1--158
Opis fizyczny
Bibliogr. 175 poz., tab., rys., wykr.
Twórcy
autor
  • Wydział Elektroniki i Technik Informacyjnych, Instytut Systemów Elektronicznych
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