Mode Recognition of Rectangular Dielectric Resonator Antenna Using Artificial Neural Network

作者：Xiao, Yuqi; Leung, Kwok Wa; Lu, Kai^*; Leung, Chi-Sing

来源：IEEE Transactions on Antennas and Propagation, 2022, 70(7): 5209-5216.

DOI：10.1109/TAP.2022.3146860

• Artificial neural networks
• Neurons
• Training
• Antenna measurements
• Resonant frequency
• Dielectric resonator antennas
• Optical resonators
• Artificial intelligence (AI)
• artificial neural network (ANN)
• dielectric resonator antenna (DRA)
• mode recognition
• particle swarm optimization (PSO)
• resonant mode

A new method powered by an artificial neural network (ANN) is studied for resonant-mode recognitions of a rectangular dielectric resonator antenna (DRA). Different rectangular DRAs were simulated with ANSYS HFSS to generate a large dataset for training the model. Their resonance frequencies, dimensions, and 3-D electric fields are input to the ANN. The output end is a 12-element array representing the corresponding probabilities of 12 different resonant modes. Using this trained ANN model, the mode recognition accuracy can reach 96.74%. Apart from identifying the resonant modes, our proposed approach can suggest how to modify a rectangular DRA to improve the purity of a resonant mode for better antenna performance.

• 单位
  中山大学