Adaptive multiparameter spectral feature analysis for synthetic aperture radar target recognition
作者: Xiangrong ZhangLicheng JiaoSisi ZhouNan ZhouJie Feng
作者单位: 1Xidian University
刊名: Optical Engineering, 2012, Vol.51 (8), pp.087203-1-087203-11
来源数据库: SPIE-the International Society for Optical Engineering
DOI: 10.1117/1.OE.51.8.087203
关键词: synthetic aperture radar automatic target recognitionspectral clusteringmultiparameter spectral feature analysisfeature extractionsupport vector machine
原始语种摘要: A feature extraction algorithm based on spectral clustering with adaptive multiparameters is proposed for synthetic aperture radar automatic target recognition (SAR-ATR). Spectral clustering has been widely applied in computer vision for its good performance. Meanwhile, the spectral mapping step in it has the property of feature space transformation. Spectral clustering based target feature extraction for SAR-ATR is constructed according to the framework of out-of-sample extensions in weighted kernel principal component analysis. To avoid the scaling parameter selection in spectral feature analysis (SFA) and eliminate the influence of scaling parameter on feature extraction performance as well, the multiple scaling parameters are calculated adaptively by local neighborhoods. Because the...
全文获取路径: SPIE 

  • recognition 识别
  • feature 结构元件
  • spectral 谱的
  • aperture 
  • scaling 按比例缩小
  • radar 雷达
  • synthetic 合成的
  • parameter 参数
  • analysis 分析
  • target 目标