Rapid Estimation Method for Coupling Degree of Airborne Antenna Based on Quantum Neural Network

• Published in: IEEE antennas and wireless propagation letters pp. 1 - 5
• Main Authors: Liu, Tian, Song, Bingbing, Meng, Fanxu, Yang, Wu, Li, Jiaqi, You, Jianwei, Lu, Weibing
• Format: Journal Article
• Language: English
• Published: IEEE 19-07-2024
• Subjects: Aircraft; antenna layout; Antennas; Atmospheric modeling; coupling degree; Couplings; electromagnetic compatibility (EMC); Logic gates; Quantum circuit; Quantum neural networks (QNN); Training
• ISSN: 1536-1225; 1548-5757
• DOI: 10.1109/LAWP.2024.3432091

Estimation of coupling degree between antennas installed on an aircraft is essential for antenna layout design, which is closely related to electromagnetic compatibility (EMC). Traditional electromagnetic (EM) methods require multiple modeling and simulation when parameters of the antenna change, which is very time-consuming and inefficient. To tackle these difficulties, a quantum neural network (QNN) is applied for the first time to estimate the coupling degree of airborne antennas and it enables the rapid prediction of dual antenna coupling under different conditions on an aircraft. The unique quantum properties and coding approaches enable a more effective capture of the characteristics of data during training, leading to the discovery of more complex patterns and correlations. Four validation sets are created for experimentation, and the proposed method demonstrates well generalization ability and fast computational speed. It showcases developmental potential comparable to that of the artificial neural network (ANN).