基于属性散射中心目标重构加权决策融合的SAR目标识别方法  

SAR Target Recognition Based on Weighted Decision Fusion of Attribute Scattering Center Target Reconstruction

作　　者：吕虎[1] LYU Hu(Nanchang Institute of Technology,Nanchang 330000 China)

机构地区：[1]南昌理工学院,南昌330000

出　　处：《电光与控制》2024年第2期112-117,124,共7页Electronics Optics & Control

摘　　要：针对合成孔径雷达(SAR)图像目标识别问题,采用原始图像及其属性散射中心目标重构结果进行决策融合。以核稀疏表示分类(KSRC)为基础分类器,对原始及重构SAR图像进行分类。KSRC通过引入核函数提升分类适应能力;目标重构可有效剔除原始SAR图像中的噪声成分。根据目标重构过程中重构结果与残差的能量关系评估原始SAR图像噪声水平,并以此为依据确定原始图像和重构图像决策结果的权重。采用加权融合手段对两个结果进行处理,判断测试样本的目标类别。基于MSTAR数据集对方法进行测试,实验结果证明了其有效性。As for target recognition in Synthetic Aperture Radar(SAR)images this paper employs the original images and the target reconstruction results based on attribute scattering centers for decision fusion.The Kernel Sparse Representation-based Classification(KSRC)is taken as the basic classifier to classify the original and reconstructed SAR images.The KSRC improves the classification adaptivity by introducing the kernel function and target reconstruction can effectively reduce noises in the original SAR images.According to the energy relationship between the reconstruction results and the residual in the target reconstruction process the noise level of the original SAR images is evaluated.Accordingly the weights of the original images and the reconstructed images are determined.The weighted fusion method is used to process them and judge the target categories of the test samples.The proposed method is tested based on MSTAR dataset and the experimental results prove its effectiveness.

关 键 词：合成孔径雷达 目标识别 属性散射中心 目标重构 KSRC 决策融合 

分 类 号：TP753[自动化与计算机技术—检测技术与自动化装置]