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A Data Driven Approach for Target Classification Based on Histogram Representation of Radar Cross Section

  • Metaadatok
Tartalom: http://hdl.handle.net/10890/40705
Archívum: Műegyetem Digitális Archívum
Gyűjtemény: 1. Tudományos közlemények, publikációk
Konferenciák gyűjteményei
1st Workshop on Intelligent Infocommunication Networks, Systems and Services, 2023
Workshop on Intelligent Infocommunication Networks, Systems and Services
Cím:
A Data Driven Approach for Target Classification Based on Histogram Representation of Radar Cross Section
Létrehozó:
Coşkun, Aysu
Bilicz, Sándor
Dátum:
2023-03-13T16:07:05Z
2023-03-13T16:07:05Z
2023
Tartalmi leírás:
A new approach for classifying targets based on their radar cross section (RCS) is discussed. The RCS presents unique statistical features depending on the target’s shape, while an incident angle with small random fluctuation is considered. Data sets are generated utilizing Physical Optics simulation of the RCS, and the classification of targets with different shapes is performed by Artificial Neural Network (ANN). The algorithm’s performance is evaluated, especially regarding the robustness against noise on the RCS data. Numerical examples motivated by mm-wave radar applications in driving assistance systems are presented. The results show that the classification algorithm performs promising results and ensures the robustness of the features extracted from histogram definitions of RCS.
Nyelv:
angol
Típus:
Konferenciaközlemény
Formátum:
application/pdf
Azonosító: