Neural Modeling of Mutual Coupling for Antenna Array Synthesis

Traditional synthesis methods usually deal with the Array Factor information or with approaches based on considering ideal radiating elements without interaction between them. Taking into account the coupling between elements increases the complexity of the synthesis tasks, so it is usually disregarded assuming a certain error in the solution. As shown in the paper, this error can be unacceptable in some antenna array designs. A neural network-based solution can exploit the "a priori" knowledge of the radiating system to relate a given radiated field distribution with the voltages that must be applied to each radiating element taking into account mutual coupling effects without increase of complexity from the designer's point of view. A set of techniques based on the use of neural networks for synthesis purposes are presented in this paper. Results of a prototype of antenna array with feeding values designed using the proposed techniques are also presented