Antenna Pattern Generation by BP Neural Network

Focus plane array has been widely used in real-time Passive millimeter wave (PMMW) imaging. But its antenna pattern nonhomogeneity because of feed lateral displacement results in space variance of point spread function (PSF) in PMMW image.In order to study the complicated space-variant law of PSF,an approach is proposed to generate antenna patterns of offset feeds by back propagation (BP) neural network.By analyzing the characteristics of data of antenna pattern,the structure with its input/output data formats of the BP network are discussed.Experimental results demonstrate that the antenna pattern generated by the neural network with double hidden layers exhibits a precision no less than 99.75%.