FDFD Simulations
收藏IEEE2026-04-17 收录
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https://ieee-dataport.org/documents/fdfd-simulations
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资源简介：
This paper presents a deep learning model for fast and accurate radar detection and pixel-level localization of large concealed metallic weapons on pedestrians walking along a sidewalk. The considered radar is stationary, with a multi-beam antenna operating at 30 GHz with 6 GHz bandwidth. A large modeled data set has been generated by running 2155 2D-FDFD simulations of torso cross sections of persons walking toward the radar in various scenarios.
提供机构：
Morgenthaler, Ann; Rappaport, Carey; Asri, Mahshid
