Optimally Synthesizing Multilayer Radar Absorbing Material (RAM) Using Artificial Bee Colony Algorithm


TOKTAŞ A., ÜSTÜN D., YİĞİT E., SABANCI K., TEKBAŞ M.

2018 XXIIIrd International Seminar/Workshop on Direct and Inverse Problems of Electromagnetic and Acoustic Wave Theory (DIPED), Tbilisi, Georgia, 24 - 27 Eylül 2018 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/diped.2018.8543261
  • Basıldığı Şehir: Tbilisi, Georgia
  • Anahtar Kelimeler: Radar absorbing material (RAM), multilayer RAM, optimization, artificial bee colony (ABC) algorithm, DESIGN
  • Bursa Uludağ Üniversitesi Adresli: Hayır

Özet

Radar absorbing material (RAM) is crucial for military vehicles that desired to be invisible to the radar systems. A vehicle coated with optimally designed multilayer RAM (MRAM) can be successfully hidden from the radar systems. At this point, optimum design of a MRAM in terms of electrical and geometric variables gains importance. In this study, variables in design of MRAM with various numbers of layers are optimally determined using artificial bee colony (ABC) which is the one of latest natural inspired algorithm. The MRAMs are considered to operate at the frequency range of 2-8 GHz and 1-20 GHz at normal incident. In optimization, a predefined material set including electrical variables existing in the literature is utilized for making a fairly comparison. The electrical variables and thickness of each layer are optimized for the objective of minimizing the reflectivity for a limited total thickness. The optimization is conducted through the formulation of impedance equivalent model in order to form the objective function. The formulation is verified through the designed MRAMs via a full wave electromagnetic solver. Moreover, a comparison is studied through the simulated MRAMs proposed in this study and the suggested ones designed using different algorithms. The proposed designs have the lest total thickness than the other ones as well as almost the same reflectivity with the best one in the literature.