Vertical Injection and Wideband Grating Coupler Based on Asymmetric Grating Trenches

A Silicon-on-insulator (SOI) perfectly vertical fibre-to-chip grating coupler is proposed and designed based on engineered subwavelength structures. The high directionality of the coupler is achieved by implementing step gratings to realize asymmetric diffraction and by applying effective index variation with auxiliary ultra-subwavelength gratings. The proposed structure is numerically analysed by using two-dimensional Finite Difference Time Domain (2D FDTD) method and achieves 76% (-1.19 dB) coupling efficiency and 39 nm 1-dB bandwidth.

Parameters Affecting the Polarity Inversion of the Vertical Electric Lightning Field to the CN-Tower

The aim of this paper is to perform a parametric study in order to analyze factors having an effect on the vertical lightning field polarization to the CN-Tower in Canada, and estimate with numerical simulation, the horizontal distance for which the reversed polarity will occur. The calculation is performed using the Finite-Difference-Time-Domain technique in two dimensions (2D-FDTD), the spatial-temporal current propagation through the lightning channel and through the high structure is represented by the lumped-series voltage-source model. The obtained results show that the vertical electric lightning field behavior has a dual polarity, the transition from a negative waveform to a positive one is observed at different observation points localized near the elevated object influencing by each modification made to the tower-parameters, the medium conductivity and the return stroke speed value. These results can contribute to the understanding of the lightning-phenomenon and allow to solve the problems of electromagnetic compatibility.

Quantifying Sub-gridding Errors in Standard and Hybrid Higher Order 2D FDTD Simulations

Sub-gridding errors for a 2D Finite-Difference Time-Domain (FDTD) simulation are compared for both the standard FDTD and Hybrid higher order FDTD cases. Subgridding contrast ratios of 1:3, 1:9, 1:15, and 1:27 are considered and analyzed. A correlation is seen between the increase of contrast ratio with the increase of sub-gridding errors for both standard and hybrid cases. However, a trend of errors reduction when using hybrid formulations over standard formulations is apparent for each contrast ratio.

Single-Sensor Source Localization Using Electromagnetic Time Reversal and Deep Transfer Learning: Application to Lightning

Electromagnetic Time Reversal (EMTR) has been used to locate different types of electromagnetic sources. We propose a novel technique based on the combination of EMTR and Machine Learning (ML) for source localization. We show for the first time that ML techniques can be used in conjunction with EMTR to reduce the required number of sensors to only one for the localization of electromagnetic sources in the presence of scatterers. In the EMTR part, we use 2D-FDTD method to generate 2D profiles of the vertical electric field as RGB images. Next, in the ML part, we take advantage of transfer learning techniques by using the pretrained VGG-19 Convolutional Neural Network (CNN) as the feature extractor tool. To the best of our knowledge, this is the first time that the knowledge of pretrained CNNs is applied to simulation-generated images. We demonstrate the skill of the developed methodology in localizing two kinds of electromagnetic sources, namely RF sources with a bandwidth of 0.1–10 MHz and lightning impulses. For the localization of lightning, based on the experimental recordings in the Säntis region, the new approach enables accurate 2D lightning localization using only one sensor, as opposed to current lightning location systems that need at least two sensors to operate.