摘要
多输入多输出合成孔径雷达(MIMO SAR)成像系统利用多通道获得人体多方位信息,适用于人体安检场景。但在太赫兹MIMO SAR成像系统中,由于天线元素数量众多,如何平衡回波信号模型的准确度与计算效率成为关键挑战。采用圆柱形合成孔径照射人体获得回波信号,并使用极坐标格式算法(PFA)处理这些回波信号,实现太赫兹三维人体成像。通过仿真比较2种不同回波信号模型:物理光学(PO)算法和射线追踪(RT)方法在计算完美电导体材料人体时的计算效率和成像效果。结果表明,使用图形处理器(GPU)加速的PO算法在计算效率和成像质量方面均表现出色,整个圆柱形合成孔径回波信号的计算时间小于1 h,同时成像结果能清晰重现危险物体的形状。此外PO算法在计算符合实际材料人体的回波信号时,同样展现出优异的性能。本文还探索了不同波瓣宽度的定向天线对成像效果的影响。该研究为未来成像算法的验证及优化提供了更准确且高效的回波信号模型。
Multiple Input Multiple Output Synthetic Aperture Radar(MIMO SAR)imaging systems use multiple channels to obtain multi-directional information about humans,which is suitable for human security scenarios.However,in THz MIMO SAR imaging systems,due to the large number of antenna elements,how to balance the accuracy and computational efficiency of the echo signal model becomes a key challenge.A cylindrical synthetic aperture is employed to irradiate the human to obtain the echo signals,and these echo signals are processed by using the Polar Format Algorithm(PFA)to achieve THz 3D human imaging.The computational efficiency and imaging results of two different echo signal models,the Physical Optics(PO)algorithm and the Ray Tracing(RT)method,are compared by simulation for computing a Perfect Electric Conductor(PEC)material-human body.The results show that the PO algorithm using Graphics Processing Unit(GPU)acceleration performs well in terms of computational efficiency and imaging quality,with less than one hour of computation time to compute the entire cylindrical synthetic aperture echo signal,and the imaging results clearly reproduce the shape of the hazardous object.In addition,the PO algorithm also performs well in calculating echo signals that match the actual material of the human body.The effect of directional antennas with different lobe widths on the imaging results is also explored.This provides a more accurate and efficient echo signal model for future validation and optimization of imaging algorithms.
作者
韩嘉越
何丹萍
朵灏
陈奔
官科
窦建武
HAN Jiayue;HE Danping;DUO Hao;CHEN Ben;GUAN Ke;DOU Jianwu(State Key Laboratory of Advanced Rail Autonomous Operation,Beijing Jiaotong University,Beijing 100044,China;School of Electronic Information Engineering,Beijing Jiaotong University,Beijing 100044,China;CTTL-Terminals,China Academy of Information and Communications Technology,Beijing 100191,China;State Key Laboratory of Mobile Network and Mobile Multimedia Technology,ZTE Corporation,Shenzhen Guangdong 518055,China)
出处
《太赫兹科学与电子信息学报》
2025年第3期202-213,共12页
Journal of Terahertz Science and Electronic Information Technology
基金
重点研发计划基金资助项目(2023YFB2904801)
教育部基金资助项目(8091B032123)
北京市自然科学基金资助项目(L221009)
航空科学基金资助项目(2022Z0660M5001)。
