A block-processing methodology to dynamically estimate and cancel systematic multiple sensor errors is proposed and analyzed. Bias estimators are obtained from sequential consecutive blocks of measurement differences, achieving an accuracy equivalent to that reachable with an extended Kalman filter (EKF) operating over each pair, but with improved computational efficiency. The algorithm is formulated generically first and then applied to solve practical problems identified when fusing data on airport surfaces: global calibration, clock shift and local systematic deviations of sensor references. Performance, with significant improvement in tracking accuracy, is illustrated in simulated representative airport scenarios, fusing data from surface movement radar (SMR) and cooperative sensors


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    On-line multi-sensor registration for data fusion on airport surface


    Contributors:


    Publication date :

    2007-01-01


    Size :

    3511440 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Contrastive Multi-Modal Fusion for Enhanced Airport Surface Surveillance

    Chao, Xu / Cai, Kaiquan / Zhao, Peng et al. | IEEE | 2025



    A Multi-Sensor Approach to Airport Surface Traffic Tracking

    Stauffer, D. / French, H. / Lenz, J. et al. | British Library Conference Proceedings | 1993