Speaker: Tian Lan

Affiliation: Beijing Institute of Technology

Academic title: Assistant Professor

Abstract:

As one of the most important non-destructive testing technologies, ground penetrating radar (GPR) technology detects the internal electromagnetic characteristics and distribution by transmitting electromagnetic waves. High-frequency electromagnetic waves have high resolution but shallow detectable depth, while low-frequency electromagnetic waves have wide detectable range but terrible resolution. In order to obtain GPR signals with both high resolution and great detectable depth, we propose a GPR multi-frequency data fusion technology based on end-to-end deep neural network. In the first part, the features of the A-scan echo signals at different scales are obtained through the convolutional layer. In the second part, these features are fused using maximum values. Finally, the high-dimensional information is decoded to return the A-scan signal. In our paper, compared with the original single-frequency signal, the fusion signal achieves higher resolution at greater depth.

Biography:

Dr. Tian Lan is engaged in radar signal processing research. He received the B.S. degree and the M.S. degree from the University of Electronic Science and Technology of China and the Ph.D. degree from Xiamen University. Currently, he is an assistant professor at Beijing Institute of Technology. He has been in charge of projects from National Nature Foundation, National Postdoctoral Foundation, Chongqing Nature Foundation, Beijing China Construction Research Institute of Building Science and Shanghai Microwave Technology Research Institute. His team has a completed ground penetrating radar(GPR) experimental platform. In the past 5 years, as the first/corresponding author, he has published 12 SCI papers in IEEE TGRS, TAP, GRSL, AWPL and other journals. He is also an independent reviewer of IEEE TGRS and GRSL.