摘要
An adaptive microwave photonic angle-of-arrival(AOA) estimation approach based on a convolutional neural network with a bidirectional gated recurrent unit(BiGRU-CNN) is proposed and demonstrated.Compared with the previously reported AOA estimation methods based on phase-to-power mapping,the proposed method is unnecessary to know the frequency of the signal under test(SUT) in advance.The envelope voltage correlation matrix is obtained from dual-drive Mach–Zehnder modulator(N-DDMZM,N > 2) optical interferometer arrays first,and then AOA estimations are performed on different frequency signals with the aid of BiGRU-CNN.A three-DDMZM-based experiment is carried out to assess the estimation performance of microwave signals at three different frequencies,and the mean absolute error is only 0.1545°.
作者
李寅
蔡乔松
杨杰
周侗
彭元喜
江天
Yin Li;Qiaosong Cai;Jie Yang;Tong Zhou;Yuanxi Peng;Tian Jiang(Institute for Quantum Information&State Key Laboratory of High Performance Computing,College of Computer Science and Technology.National University of Defense Technology,Changsha 410073,China;National nnovation Institute of Defense Technology.Academy of Military Sciences PLA China,Beijing 100071,China;Bejing Institute for Advanced Stuy,Natinal university of Defense Technology,Beijing 100000,China;Insttute for Quantum Science and Technogy,Colege of Since,National Universty of Dfese Techogy,Changsha 40073,China)
基金
supported by the National Natural Science Foundation of China (Nos.61801498 and 62075240)
the National Key Research and Development Program of China (No.2020YFB2205804)。
