Convolutional Perfectly Matched Layer for an Unconditionally Stable LOD-FDTD Method

摘要

This letter presents the development and implementation of the convolutional perfectly matched layer (CPML) for the recently proposed locally 1-D finite difference time domain method (LOD–FDTD. Two different examples are simulated. Their results are compared with the FDTD–PML method and it is found that the proposed method has 16 dB less reflection error at a Courant Friedrich Levy number of one.