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

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.