Radar target detection by using Levenberg-Marquardt algorithm

• Autorzy: Nasret Ali Najdet , Kamal Ayoub Esam , Mahmood Zuhiar Shakor

Identyfikatory

DOI

10.15199/48.2023.03.47

Warianty tytułu

PL

Wybór procedury optymalizacyjnej dla systemu CAD

• Języki publikacji: EN

Abstrakty

EN

Typically, with radar systems, a person is required to assist in the process of detecting a target. As a result of this human factor, radar systems are not completely dependable since their performance differs across operators. In this work, an intelligent radar system for border monitoring is described. Artificial neural networks trained using the Levenberg-Marquardt technique have been used to identify and categorize targets automatically in the radar system under development. Inverse Synthetic Aperture Radar images captured with high resolution by the radar’s detecting module serve as both input and output data for the neural network. The simulation findings show that intelligent radar can identify various targets. Both human operators and a competing radar system were no match for the radar’s efficiency.These findings suggest that in the future, intelligent technologies may be able to take the position of human radar operators in high-risk security environments.

PL

Zazwyczaj w przypadku systemów radarowych wymagana jest osoba do asystowania w procesie wykrywania celu. W wyniku tego czynnika ludzkiego systemy radarowe nie s ˛a całkowicie niezawodne, poniewaz ich wydajno ˙ s´c ró ´ zni si ˛ ˙ e w zalezno ˙ sci od operatora. W pracy ´ opisano inteligentny system radarowy do monitorowania granic. Sztuczne sieci neuronowe wyszkolone przy uzyciu techniki Levenberga-Marquardta ˙ zostały wykorzystane do automatycznej identyfikacji i kategoryzacji celów w opracowywanym systemie radarowym. Obrazy radaru z odwrócon ˛a syntetyczn ˛a apertur ˛a zarejestrowane w wysokiej rozdzielczosci przez moduł wykrywaj ˛ ´ acy radaru słuz ˛ ˙a zarówno jako dane wejsciowe, jak i wyj ´ sciowe ´ dla sieci neuronowej. Wyniki symulacji pokazuj ˛a, ze inteligentny radar mo ˙ ze identyfikowa ˙ c ró ´ zne cele. Zarówno operatorzy, jak i konkurencyjny system ˙ radarowy nie dorównali wydajnosci radaru. Odkrycia te sugeruj ˛ ´ a, ze w przyszło ˙ sci inteligentne technologie mog ˛ ´ a zaj ˛ac miejsce operatorów radarów w ´ srodowiskach wysokiego ryzyka.( Radarowe wykrywanie celu za pomoc ˛ ´ a algorytmu Levenberga-Marquardta).

Słowa kluczowe

EN

Doppler information; high range resolution; surveillance; automatic radar target recognition; Neural Networks

PL

system CAD; systemy radarowe; sieci neuronowe

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2023
• Tom: R. 99, nr 3
• Strony: 265--270
• Opis fizyczny: Bibliogr. 16 poz., rys., tab.

Twórcy

autor

Nasret Ali Najdet

• Kerkuk Technical Institute , Electronic Technology Department , Northern Technical University , Musul. Iraq

autor

Kamal Ayoub Esam

• Kerkuk Technical Institute , Electronic Technology Department , Northern Technical University , Musul. Iraq

autor

Mahmood Zuhiar Shakor

• Kerkuk Technical Institute , Electronic Technology Department , Northern Technical University , Musul. Iraq

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).