Power optimization of reconfigurable aperture of electrically driven antenna array

Apertures of electrically driven antenna arrays can be reconfigured for optimized power distribution. The benefit is dynamically controlled power availability, which makes the system efficient. In this paper we describe such a dynamic mechanism based on Artificial Neural Network (ANN) which formulates a dynamic regulatory scheme for an electrically driven antenna array. An ANN in feed-forward structure called Multilayer Perceptron (MLP) is trained to track the non-linear relationship between antenna geometry and distance between target and receiver antenna. This ANN based arrangement designed for an antenna optimizes the power usage and leads to energy saving with dynamic aperture reconfiguration. The advantage of the system is its adaptive processing which leads to considerable amount of saving of design time compared to traditional optimization techniques.