Coupling Matrix Extraction of Microwave Filters by Using One-Dimensional Convolutional Autoencoders - Zhang, Yongliang; Wang, Yanxing; Yi, Yaxin; Wang, Junlin; Liu, Jie; Chen, Zhixi (Frontiers in Physics, 2021)
The tuning of microwave filter is important and complex. Extracting coupling matrix from given S-parameters is a core task for filter tuning. In this paper, one-dimensional convolutional autoencoders(1D-CAE) is proposed to extract coupling matrix from S-parameters of narrow band cavity filter and apply this method to the computer-aided tuning (CAT) process. The training of 1D-CAE model consists of two steps. First, in the encoding part, one-dimensional convolutional neural network (1D-CNN) with several convolution layers and pooling layers are used to extract the coupling matrix from the S-parameters during the microwave filters tuning procedure. Second, in the decoding part, several full connection layers are employed to reconstruct the S-parameters to ensure the accuracy of extraction. The S-parameters obtained by measurement or simulation exists phase shift, so the influence of phase shift must be removed. The efficiency of the presented method in this paper is validated by a sixth order cross-coupled filter simulation model tuning example.