An Intelligent Antenna Synthesis Method Based on Machine Learning

An intelligent antenna synthesis method is proposed to automatically select suitable antenna type and provide optimal geometric parameters according to the requirement of antenna performance. The performance characteristics of different antennas are analyzed, and a smart antenna selection model is established to recommend the appropriate antenna by using support vector machine (SVM). Then, the stacking ensemble model is built by combining five primary learners to give full play to the advantages of each type of learners and, finally, the geometric parameters of the antenna are provided. Microstrip patch antenna, spiral antenna, and horn antenna are used to demonstrate the accuracy and efficiency of the model. The system shows a great ability of antenna classification with accuracy over 99% and parameter prediction with a mean absolute percentage error (MAPE) of less than 6%. Moreover, the results are compared with the traditional data-driven model, and the key parameters of the model are comprehensively discussed. The proposed method could be widely used in intelligent antenna design in practice.