现代应用物理2025，Vol.16Issue(2)：209-215,7.DOI:10.12061/j.issn.2095-6223.202409028
应用于馈源失配天线的人工神经网络单脉冲测角方法
Monopulse Angle Measurement Method for Feed Mismatch Antenna Based on Artificial Neural Network
摘要
Abstract
To address the increased angle measurement deviation caused by feed mismatch in monopulse antennas,a monopulse angle measurement module for angle measurement based on artificial neural network(ANN)is constructed.The module uses the complex ratios of the elevation difference channel and the azimuth difference channel to the sigma channel,which are received by the 5-horn antenna as the inputs of the neural network,and the elevation angle and the azimuth angle as the output of the network.The design can integrate channel calibration and angle calibration,and is suitable for monopulse angle measurement in the case of feed mismatch.The experimental results show that,compared to traditional angle discrimination curve-based methods,the ANN-based angle measurement module can significantly restrain the deviation of angle measurement.The accuracy of pitch angle and azimuth angle measurement is increased by 76.84％and 87.96％,respectively.关键词
单脉冲测角/馈源失配/人工神经网络Key words
monopulse/feeder mismatch/artificial neural network(ANN)分类
电子信息工程引用本文复制引用
汪海波,戎磊,梅楷,吕东辉,张荣威,巴涛..应用于馈源失配天线的人工神经网络单脉冲测角方法[J].现代应用物理,2025,16(2):209-215,7.基金项目
先进高功率微波技术重点实验室基金资助项目 （）
