基于PCA-LDA-SVM的多普勒雷达车型识别算法
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中国科学院上海微系统与信息技术研究所,中国科学院上海微系统与信息技术研究所

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国家高技术研究发展计划(863计划)


Vehicle Recognition algorithm with Doppler Radar Based on PCA-LDA-SVM
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Chinese Academy of Sciences,Shanghai In stitute of Microsystem and Information Technology Institute Shanghai, the Graduate School of Chinese Academy of Sciences BeiJing, shang hai huichang intelligent transportation system coLTD,Shanghai,Chinese Academy of Sciences,Shanghai In stitute of Microsystem and Information Technology Institute Shanghai, the Graduate School of Chinese Academy of Sciences BeiJing, shang hai huichang intelligent transportation system coLTD,Shanghai

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The National High Technology Research and Development Program of China (863 Program)

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    摘要:

    车辆检测和车型识别是智能交通系统(ITS)中的一个重要方面,而目标识别是低分辨率雷达领域的一个难点。该文提出一种用多普勒雷达进行车型识别的方法,把车辆建模成包含多个散射中心的目标体,散射中心与雷达的距离与频谱能量有关,因此同一目标的频谱变化反映了该目标长高等轮廓特征。然后将有效的频谱特征结合主成分分析(PCA)和线性判别分析(LDA)进行降维,再利用支持向量机(SVM)等分类器实现分型。最后,文章对不同识别算法交叉验证的实验结果进行比较,表明基于PCA-LDA-SVM的车型识别算法效果理想,有广泛的应用前景。

    Abstract:

    Vehicle detection and recognition is of great importance to the development of Intelligent Transportation System(ITS),but Target Recognition is a challenging problem for low_resolution Radar. This paper proposes a Vehicle Recognition approach using Doppler Radar, and the spectrum variation of one vehicle reflects its outline. Then, the dimension of effective spectrum feature can be reduced by the methods of Principal Component Analysis(PCA) and Linear Discriminant Analysis(LDA), then vehicles can be classified into three types by classifier algorithms such as Support Vector Machine(SVM), k-Nearest Neighbor(KNN). At last, the paper compares the experiment results of different algorithms by cross validation, and shows the algorithm based on PCA-LDA-SVM can achieve ideal result.

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方菲菲,余稳.基于PCA-LDA-SVM的多普勒雷达车型识别算法[J].数据采集与处理,2012,27(1):

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  • 收稿日期:2011-05-23
  • 最后修改日期:2011-09-09
  • 录用日期:2011-10-25
  • 在线发布日期: 2012-08-21