In radar target tracking, knowledge of the true dynamics of target motion is paramount for accurate state estimates. Target maneuvers complicate this knowledge due to quick unknown changes in the target's dynamics. Many popular methods for detecting target maneuvers utilize an input estimation approach where the input to the target's state system is estimated. While input estimation methods work well, they are limited to lower data rate systems due to their complexity. In this work, we propose a new method of target maneuver detection using symbolic dynamics. Symbolic dynamics has the advantage of being computationally simple due to the way it symbolizes and compresses the data. We develop a new radar target maneuver detector leveraging symbolic dynamics. Through two different simulations, we demonstrate the ability of the symbolic dynamics detector to be as fast as a simple chi-squared detector while simultaneously detecting maneuvers sooner and with higher accuracy.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Symbolic Dynamics for Radar Target Maneuver Detection With High Data Rates


    Beteiligte:


    Erscheinungsdatum :

    01.04.2024


    Format / Umfang :

    2122729 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Symbolic dynamics for radar target maneuver detection

    Singerman, Paul G. / O'Rourke, Sean M. / Narayanan, Ram M. et al. | British Library Conference Proceedings | 2021


    Detection of Target Maneuver Onset

    Jifeng Ru, / Jilkov, V.P. / Rong Li, X. et al. | IEEE | 2009


    Detection of Target Maneuver Onset

    Ru, J. | Online Contents | 2009


    Target Turning Maneuver Detection using High Resolution Doppler Profile

    Yilong Zhu / Hongqi Fan / Jianpeng Fan et al. | IEEE | 2012


    Maneuver Detection with Two Mixture-Based Metrics for Radar Track Data

    Montilla, Jose M. / Vazquez, Rafael / Di Lizia, P. | AIAA | 2025