For an airborne sensor, there is a pressing need to be able to detect/track submerged submarines, shipwrecks, sea mines, unexploded explosive ordnance, and buried drums during maritime surveillance. Traditional usage is the magnetic anomaly detection (MAD), where the small changes in the earth's magnetic field caused by the ferrous components of the targets are measured. The primary means of long-range detection and classification of targets are with passive and active acoustic sensors, and MAD is used for accurate final localization. MAD could also be used for land-based targets but this is not common. Knowing the relationship between the magnetic signature and the kinematic parameters, the tracking problem can be formulated under a Bayesian framework. In this article, multiple nonlinear filters are used for a real single surface-target tracking problem in maritime surveillance using an airborne total-field sensor. The posterior Cramér–Rao lower bound for MAD is derived. Given the total-field measurements, these filters can estimate the kinematic states as well as the permanent moments and induced moments effectively. Results demonstrate the effectiveness of the proposed nonlinear filters as well as the impact of using MAD as part of airborne surveillance.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Airborne Maritime Surveillance Using Magnetic Anomaly Detection Signature




    Erscheinungsdatum :

    01.10.2020


    Format / Umfang :

    2476527 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Advances in airborne maritime surveillance radar

    Watts, S. / Gordon, A. / Jolley, A. et al. | British Library Conference Proceedings | 1999


    OCULUS Sea™ Forensics: An Anomaly Detection Toolbox for Maritime Surveillance

    Thomopoulos, Stelios C. A. / Rizogannis, Constantinos / Thanos, Konstantinos Georgios et al. | Springer Verlag | 2019




    Airborne Magnetic Anomaly Navigation

    Canciani, Aaron / Raquet, John | IEEE | 2017