Tree trunk inspections using a polarimetric GPR system
In this work, a novel signal processing framework for polarimetric GPR measurements is presented for inspection of tree trunks’ decay. The framework combines a polarimetric noise filter and an arc-shaped diffraction imaging algorithm. The polarimetric noise filter can increase the signal-to-noise ratio (SNR) of B-scans caused by the bark and the high-loss propriety of the tree trunk based on a 3D Pauli feature vector of the Bragg scattering theory. The arc-shaped diffraction stacking and an imaging aperture are then designed to suppress the effects of the irregular shape of the tree trunk on the signal. The proposed detection scheme is successfully validated with real tree trunk measurements. The viability of the proposed processing framework is demonstrated by the high consistency between the results and the real-truth trunk cross-sections.
Univ. of West London (United Kingdom)
Lilong Zou received the B.S. and M.S. degrees from Jilin University, Changchun, China, in 2009 and 2012, respectively, and the Ph.D. degree from Tohoku University, Sendai, Japan, in 2016. From 2016 to 2018, he was an assistant professor with Tohoku University, Japan. From 2018 to 2019, he was a researcher with the National Institute of Advanced Industrial Science and Technology, Koriyama, Japan. He is currently a Research Fellow with University of West London, London, U.K.. His research interests include signal processing technology of ground penetrating radar (GPR), and ground-based synthetic aperture radar (GB-SAR) for disaster mitigation and nondestructive testing.
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