Monostatic microwave imaging method for conductor cylinder based on neural network

A microwave imaging method for monostatic using neural network is proposed in this paper.Firstly,the TM mode scattering data of different shapes of conductor cylinder are obtained by finite-difference time-domain(FDTD)method.And all these data are taken as training samples for neural network.A hybrid self-learning strategy based on integral differential evolution strategy and BP algorithm is presented, which can improve self-learning capability of system and overcome the drawbacks of single BP neural network, such as slow astringency.Finally,the satisfactory results of two-dimensional microwave imaging are reached by using the optimized neural network.