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  • 1.
    Burak Guldogan, Mehmet
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Orguner, Umut
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gaussian mixture PHD filter for multi-target tracking using passive doppler-only measurements2012In: IET Conference Publications: vol 2012, issue 595 CP, IEEE conference proceedings, 2012, Vol. 2012, no 595 CP, p. 1-6Conference paper (Refereed)
    Abstract [en]

    In this paper, we analyze the performance of the Gaussian mixture probability hypothesis density (GM-PHD) filter in tracking multiple non-cooperative targets using a passive sensor network. Non-cooperative transmissions from illuminators of opportunity like GSM base stations, FM radio transmitters or digital broadcasters are exploited by non-directional separately located Doppler measuring sensors. Clutter, missed detections and multi-static Doppler variances are incorporated into a realistic multi-target scenario. Simulation results show that the GM-PHD filter successfully tracks multiple targets using only Doppler shift measurements in a passive multi-static scenario.

  • 2.
    Guldogan, Mehmet Burak
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Orguner, Umut
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Björklund, Svante
    Swedish Defence Research Agency, Linköping, Sweden.
    Petersson, H.
    Swedish Defence Research Agency, Linköping, Sweden.
    Nezirovic, A.
    Swedish Defence Research Agency, Linköping, Sweden.
    Human gait parameter estimation based on micro-doppler signatures using particle filters2011In: Acoustics, Speech and Signal Processing (ICASSP), 2011, IEEE , 2011, p. 5940-5943Conference paper (Refereed)
    Abstract [en]

    Monitoring and tracking human activities around restricted areas is an important issue in security and surveillance applications. The movement of different parts of the human body generates unique micro-Doppler features which can be extracted effectively using joint time-frequency analysis. In this paper, we describe the simultaneous tracking of both location and micro-Doppler features of a human using particle filters (PF). The results obtained using the data from a 77 GHz radar prove the successful usage of particle filters in tracking micro-Doppler features of the human gait.

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