Augmented doppler filter bank based approach for enhanced targets detection

• Autorzy: Mostafa Mostafa M. , Shaker Mahmoud , Zahran Shady , Nasr Mohamed EL-Said , Hamdi Azhar A.

Identyfikatory

DOI

10.15199/48.2023.08.11

Warianty tytułu

PL

Podejście oparte na rozszerzonym banku filtrów dopplerowskich do ulepszonego wykrywania celów

• Języki publikacji: EN

Abstrakty

EN

Radar Target Detection (RTD) is considered to be one of the most essential parts of modern radar systems. In typical radars, detecting targets in noise is difficult. Conventional radar signal processing approaches such as Constant False Alarm Rate (CFAR) are adopted in an attempt to improve the Signal-to-Noise Ratio (SNR). However, due to the severity of the harsh and complex environments in the radar measurements, the target detection problem becomes extremely challenging when employing such traditional approaches. Therefore, developing a reliable and robust RTD technique is essential. In this paper, an augmented Doppler Filter Bank (DFB) based approach has been proposed to handle the associated radar drawbacks in such a complicated scenario, by incorporating the computer vision algorithms in order to separate the moving targets from the noisy background through a real radar dataset. A Frequency Modulated Continuous Wave (FMCW) radar has been mounted on an Unmanned Aerial Vehicle (UAV) for ground targets detection purposes. A real flight has been conducted in a challenging environment to assess the performance of the proposed system. The experimental results demonstrate the ability of the proposed system to enhance the estimated forward velocity to 82.8% over the conventional DFB with the CFAR detector.

PL

Radarowe wykrywanie celu (RTD) jest uważany za jedną z najważniejszych części nowoczesnych systemów radarowych. W typowych radarach wykrywanie celów w hałasie jest utrudnione. Konwencjonalne podejścia do przetwarzania sygnału radarowego, takie jak stała częstotliwość fałszywych alarmów (CFAR), są stosowane w celu poprawy stosunku sygnału do szumu (SNR). Jednak ze względu na surowość trudnych i złożonych środowisk w pomiarach radarowych, problem wykrywania celu staje się niezwykle trudny przy stosowaniu takich tradycyjnych podejść. Dlatego niezbędne jest opracowanie niezawodnej i solidnej techniki BRT. W tym artykule zaproponowano podejście oparte na rozszerzonym banku filtrów dopplerowskich (DFB), aby poradzić sobie z powiązanymi wadami radaru w tak skomplikowanym scenariuszu, poprzez włączenie algorytmów widzenia komputerowego w celu oddzielenia ruchomych celów od hałaśliwego tła za pomocą prawdziwego radaru zestaw danych. Radar fali ciągłej z modulacją częstotliwości (FMCW) został zamontowany na bezzałogowym statku powietrznym (UAV) w celu wykrywania celów naziemnych. Aby ocenić działanie proponowanego systemu, przeprowadzono prawdziwy lot w trudnym środowisku. Wyniki eksperymentów pokazują zdolność proponowanego systemu do zwiększenia szacowanej prędkości do przodu do 82,8% w porównaniu z konwencjonalnym DFB z detektorem CFAR.

Słowa kluczowe

EN

constant false alarm rate; doppler filter bank; moving target detector; radar signal processing

PL

stała częstość fałszywych alarmów; bank filtrów dopplerowskich; wykrywacz ruchomych celów; przetwarzanie sygnału radarowego

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2023
• Tom: R. 99, nr 8
• Strony: 67--73
• Opis fizyczny: Bibliogr. 25 poz., rys., tab.

Twórcy

autor

Mostafa Mostafa M.

• Electronics and Electrical Communications Engineering Dept., Air Defence Collage, Alexandria, Egypt

autor

Shaker Mahmoud

• Electronics and Electrical Communications Engineering Dept., Air Defence Collage, Alexandria, Egyp

autor

Zahran Shady

• Department of Geomatics, University of Calgary, Calgary, Canada

autor

Nasr Mohamed EL-Said

• Electronics and Electrical Communications Engineering Dept., Faculty of Engineering, Tanta University, Tanta 31527, Egypt

autor

Hamdi Azhar A.

• Department of Electronics and Communication, Zagazig University, Egypt

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).