| 引用本文: | 王世晞,贺志国.基于PCA特征的快速SAR图像目标识别方法.[J].国防科技大学学报,2008,30(3):136-140.[点击复制] |
| WANG Shixi,HE Zhiguo.The Fast Target Recognition Approach Based on PCA Features for SAR Images[J].Journal of National University of Defense Technology,2008,30(3):136-140[点击复制] |
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| 基于PCA特征的快速SAR图像目标识别方法 |
| 王世晞, 贺志国 |
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(国防科技大学 电子科学与工程学院，湖南 长沙 410073)
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| 摘要: |
| 目标识别是SAR图像解译的重要一环，受到广泛的关注，而实时性又是评估目标识别系统性能的主要指标之一。从实时的角度出发，提出了一种快速的SAR目标识别方法。该方法采用基于Hebb学习规则的主分量分析（PCA）进行特征提取，使用多层感知器神经网络（MLP NN）进行目标分类。实验结果表明，在维持较好识别性能的前提下，该方法具有内存需求少、运行速度快的特点，能用于实时处理。 |
| 关键词: 目标识别 特征提取 PCA 合成孔径雷达 神经网络 |
| DOI： |
| 投稿日期：2008-04-23 |
| 基金项目: |
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| The Fast Target Recognition Approach Based on PCA Features for SAR Images |
| WANG Shixi, HE Zhiguo |
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(College of Electronic Science and Engineering, National Univ. of Defense Technology, Changsha 410073, China)
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| Abstract: |
| The extensively focused target recognition is one of the important problems for SAR imagery interpretation. With the aim to real-time processing, a fast SAR target recognition system is built, which utilizes the principal component analysis (PCA) for feature extraction and a multi-layer neural network (MLP NN) as the classifier. The experimental results show that it consumes little memory and runs very fast, thus can be used in the real-time situation. |
| Keywords: target recognition feature extraction PCA SAR neural network |
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