CAE Proceedings on International Conference on Communication Technology |
Foundation of Computer Science USA |
ICCT2015 - Number 1 |
February 2016 |
Authors: Amit A. Deshmukh, Shivali D. Kulkarni, Venkata A.p.c. |
712e497a-579d-4241-a865-52b8dcfd54b0 |
Amit A. Deshmukh, Shivali D. Kulkarni, Venkata A.p.c. . Artificial Neural Network Model for Suspended Shorted 900 Sectoral Microstrip Antennas. CAE Proceedings on International Conference on Communication Technology. ICCT2015, 1 (February 2016), 0-0.
The simplest way to realize broadband microstrip antenna is by selecting thicker air substrate for the radiating patch. The compact circular microstrip antenna is realized by placing the shorting plate/post along the zero field line at fundamental TM11 mode and by using only half of the shorted patch. To increase the bandwidth of compact shorted microstrip antenna, thicker air substrate is used. While designing shorted circular microstrip antenna, frequency formulations used in for conventional circular microstrip antenna on thinner substrate, gives closer approximation. However design formulations to realize shorted compact circular microstrip antenna on thicker substrate over wide range of frequencies are not available. In this paper, an artificial neural network model to predict the shorted circular patch radius in shorted 900 Sectoral microstrip antenna for varying frequencies and substrate thickness is proposed. The frequency calculated using the predicted shorted patch radius closely agrees with the simulated and measured shorted patch frequency.