Two contrasting approaches for tracking multiple targets in multi-beam forward-looking sonar images are considered. The first approach is based on assigning a Kalman filter to each target and managing the measurements with gating and a measurement-to-track data association technique. The second approach uses the recently developed particle implementation of the multiple-target probability hypothesis density (PHD) filter and a target state estimate-to-track data association technique. The two approaches are implemented and compared on both simulated sonar and real forward-looking sonar data obtained from an autonomous underwater vehicle (AUV) and demonstrate that the PHD filter with data association compares well with traditional approaches for multiple target tracking


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Particle PHD filter multiple target tracking in sonar image


    Contributors:
    Jeong, T.T. (author)


    Publication date :

    2007-01-01


    Size :

    1114595 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Problems in multi-target sonar tracking

    Fortmann, T.E. / Baron, S. | Tema Archive | 1978


    Two-Layer Particle Filter for Multiple Target Detection and Tracking

    Garcia-Fernandez, A. F. / Grajal, J. / Morelande, M. R. | IEEE | 2013