This article considers radar detection and tracking of weak fluctuating targets using dynamic programming (DP)-based track-before-detect (TBD). The clutter is modeled using a Weibull distribution, and the well-known Swerling type 0, 1, and 3 targets are considered. An efficient algorithm is proposed, which employs order statistics in DP-based TBD to detect weak fluctuating targets. In addition, a novel expanding window track-before-detect (EW-TBD) technique for multiframe processing is presented to improve the detection performance with reasonable computational complexity compared to batch processing. It is shown that EW-TBD has lower complexity than existing multiframe processing techniques. Simulation results are presented, which confirm the superiority of the proposed expanding window technique in detecting targets even when they are not present in every scan in the window. In addition, the throughput of the proposed technique is higher than that with batch processing.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Expanding Window Dynamic-Programming-Based Track-Before-Detect With Order Statistics in Weibull Distributed Clutter


    Contributors:


    Publication date :

    2020-08-01


    Size :

    2864937 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Track-Before-Detect Strategies for Radar Detection in G0-Distributed Clutter

    Wei Yi / Haichao Jiang / Kirubarajan, Thia et al. | IEEE | 2017


    Weibull-Distributed Ground Clutter

    Sekine, M. / Ohtani, S. / Musha, T. et al. | IEEE | 1981


    On Weibull-Distributed Weather Clutter

    Sekine, Matsuo / Musha, Toshimitsu / Tomita, Yuichi et al. | IEEE | 1979


    Track-before-detect for sea clutter rejection: tests with real data

    Aprile, Angelo / Grossi, Emanuele / Lops, Marco et al. | IEEE | 2016