Design of multiple function antenna array using radial basis function neural network

• Autor(a) principal: Reddy,B Rama Sanjeeva
• Data de Publicação: 2013
• Outros Autores: Vakula,D, Sarma,N.V.S.N
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Journal of Microwaves. Optoelectronics and Electromagnetic Applications
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-10742013000100016
• topic: Artificial Neural Network (ANN); Half power beam width (HPBW); Multiple Function Antenna (MFA); Radial Basis Function (RBF)

A novel approach to design Multiple Function Antenna (MFA) arrays using Artificial Neural Networks is suggested. A planar array with uniform current excitations which can generate different beam widths and gains is designed using Artificial Neural Networks. The desired beam width, gain and number of elements are given as input to the neural network. The output of the neural network is the current excitations in the form ON/OFF state of the array. Radial Basis Function Neural Network (RBFNN) is initially trained with the input-output data pairs and tested. The network showed 98% high success rate.