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    Progress on using principle component analysis in FSR for vehicle classification

    Progress on using principle component analysis in FSR for vehicle classification


    This paper presents a simple Forward Scattering Radar (FSR) and describes its application for automatic road vehicle classification. It introduces the radar itself and the targets classification system. For classification, the authors propose a system which extracts features from radar measurements, uses Fourier Transform and Principle Component Analysis (PCA) to transform these features prior to using the k-nearest neighbour classifier. By analysing 850 experimentally obtained car signatures, the effectiveness of the system is confirmed. This paper is a continuation of the work dedicated to the vehicles classification using FSR first introduced at the VehCom conference.

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    Titel :

    Progress on using principle component analysis in FSR for vehicle classification

    Weitere Titelangaben:

    Fortschritte bei der Anwendung der grundlegenden Komponenten-Analyse im System des vorwärts gerichteten Radars zur Fahrzeugklassifizierung

    Beteiligte:
    Abdullah, R.S.A. Raja (Autor:in) / Cherniakov, M. (Autor:in) / Jancovic, P. (Autor:in) / Salous, M. (Autor:in)
    Erschienen in:

    WIT, International Workshop on Intelligent Transportation, 2 ; 7-11

    Erscheinungsdatum :

    2005

    Format / Umfang :

    5 Seiten, 6 Bilder, 3 Tabellen, 5 Quellen

    Medientyp :

    Aufsatz (Konferenz)

    Format :

    Print

    Sprache :

    Englisch

    Schlagwörter :

    Fahrzeugwarngerät , Fahrzeugelektronik , Radarüberwachung , Fahrzeugerkennungszahl , mathematisches Modell

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