DocumentCode
3749849
Title
Detection and classfication of subsurface objects by polarimetric radar imaging
Author
Christian N. Koyama;Motoyuki Sato
Author_Institution
Center for Northeast Asian Studies, Tohoku University Sendai, Miyagi, Japan
fYear
2015
Firstpage
440
Lastpage
445
Abstract
The paper addresses the problem of subsurface object detection by polarimetric synthetic aperture radar (PolSAR) imaging. We are developing methods to detect persons and objects buried below-ground from low-frequency ground-based (GB), airborne and spaceborne SAR. An L-band GB-SAR system for fast aerial imaging is under development. Airborne and spaceborne radar imaging data was acquired by the Japanese Pi-SAR-L2 and ALOS-2 (both operated by JAXA), respectively. Both systems operate in the L-band with a center frequency of 1.25 GHz and provide quad-pol data with 3 m resolution. Reflector targets were buried at various depth at a sand beach to investigate the penetration capabilities. Preliminary results indicate that for soils with low permittivity the L-band SAR can detect such targets up to a depth of 20 cm. In addition we present results obtained with a novel polarimetric ultra-wideband (UWB) GB-SAR system developed by our group. This system for polarimetric near-range subsurface imaging of building structures uses a circular polarization spiral antenna array operating in the 5-15 GHz band. By 2 dimensional scanning, 3D subsurface images with super high resolution of 1 cm can be acquired. Based on experimental results from UWB GB-SAR measurements, we discuss the potential to classify subsurface objects by detailed analysis of their scattering behavior. A simple preliminary classification approach based on measured polarimetric signatures is proposed. The results demonstrate the unique potential of high-resolution polarimetric radar imaging to locate and classify subsurface objects by using the information about their scattering mechanisms.
Keywords
"Decision support systems","Antennas","L-band","Soil","Surface waves","Sea surface"
Publisher
ieee
Conference_Titel
Radar Conference, 2015 IEEE
Type
conf
DOI
10.1109/RadarConf.2015.7411924
Filename
7411924
Link To Document