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高分辨力极化SAR图像城市区域车辆目标检测
Vehicle detection over urban areas in high resolution polarimetric SAR images
投稿时间:2018-03-08  修订日期:2018-04-13
中文关键词:高分辨力  极化合成孔径雷达  城市区域  车辆检测  深度卷积神经网络
英文关键词:high resolution  polarimetric Synthetic Aperture Radar(SAR)  urban areas  vehicle detection  deep convolutional neural network
基金项目:国家自然科学基金资助项目(61771043;61490693);高分辨率对地观测系统重大专项资助项目(41-Y20A14-9001-15/16;30-Y20A12-9004-15/16;03-Y20A10-9001-15/16)
作者单位
高军山 1.Department of Electrical EngineeringTsinghua UniversityBeijing 100084China2. The Second LaboratoryTroops 63892 of PLALuoyang Henan 471003China 
陈 杭 Department of Electrical EngineeringTsinghua UniversityBeijing 100084China 
林慧平 Department of Electrical EngineeringTsinghua UniversityBeijing 100084China 
殷君君 School of Computer and Communication EngineeringUniversity of Science & Technology BeijingBeijing 100083China 
杨 健 Department of Electrical EngineeringTsinghua UniversityBeijing 100084China 
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中文摘要:
      研究基于高分辨力极化合成孔径雷达(SAR)图像的城市区域车辆目标自动检测方法。城市区域具有复杂的地物,这给在城市区域进行车辆目标检测工作带来困难。首先采用Freeman-Durden分解、极化白化滤波器(PWF)和相似性参数3种方法来提取图像数据的极化信息;在此基础上,采用深度卷积神经网络来对车辆目标和其他地物进行二分类,实现对城市区域车辆目标的检测。基于机载分米级分辨力极化SAR数据的实验结果验证了该方法的有效性,在较低的虚警率下获得较高的检测率。将3种极化特征融合时,能够在虚警率为2.82%时获得95.65%的检测率。
英文摘要:
      The automatic detection of vehicles over urban areas is studied based on airborne decimeter resolution polarimetric Synthetic Aperture Radar(SAR) data. Urban areas are characterized by complex ground objects, which makes the detection of vehicles particularly challenging. Firstly, several classes of polarization information are extracted, including those from Freeman-Durden decomposition, Polarization Whitening Filter(PWF) and similarity parameters. Then, deep convolutional neural network algorithm is adopted to classify vehicle targets and other objects to realize the detection of vehicle targets in urban areas. Using experiments based on airborne decimeter resolution polarimetric SAR data, high detection rate under low false alarm rate can be obtained, demonstrating the effectiveness of the proposed method. When the three polarization characteristics are combined, the detection rate of 95.65% can be reached when the false alarm rate is 2.82%.
引用本文:高军山,陈 杭,林慧平,殷君君,杨 健.高分辨力极化SAR图像城市区域车辆目标检测[J].太赫兹科学与电子信息学报,2018,16(4):603~608
DOI:10.11805/TKYDA201804.0603
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