Asan important means in low-altitude airspace surveillance, passive radar has been widely studied. With the increasing complexity of the low-altitude environment, the urgent need for radar's capability of automatic target recognition (ATR) emerges. In the field of ATR for passive radar, the method based on radar cross section (RCS) is an important direction for the simplicity of feature extraction. In this article, we exploit the compensated quasi-echo-power (CQEP), i.e., quasi-RCS, to realize ATR in passive radar. We propose an ATR method on the basis of the angular diversity. First, we divide the angular space, which consists of four components of the incident angle and scattering angle of electromagnetic wave, into multiple subspaces. Then, we build a subrecognizer in each angular subspace according to the CQEP distribution characteristics. Each receiving station of the multistatic passive radar recognizes targets in an angular subspace corresponding to its observation and outputs a preliminary decision. Based on the preliminary decisions of all receiving stations, a voting strategy is adopted to make the final decision on the unknown target class in the fusion center. Experimental results based on real-life target data show that the proposed method has a significant improvement on the average correct recognition rate with fusion of three receiving stations, which validates the proposed method.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Automatic Target Recognition Based on RCS and Angular Diversity for Multistatic Passive Radar


    Beteiligte:
    Cao, Xiaomao (Autor:in) / Yi, Jianxin (Autor:in) / Gong, Ziping (Autor:in) / Wan, Xianrong (Autor:in)


    Erscheinungsdatum :

    01.10.2022


    Format / Umfang :

    5138318 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Target Kinematic State Estimation With Passive Multistatic Radar

    Ma, Hui / Antoniou, Michail / Stove, Andrew G. et al. | IEEE | 2021



    Adaptive Channel Assignment for Maneuvering Target Tracking in Multistatic Passive Radar

    Dai, Jinhui / Yan, Junkun / Pu, Wenqiang et al. | IEEE | 2023


    Multistatic target tracking for passive radar in a DAB/DVB network: initiation

    Choi, Sora / Crouse, David / Willett, Peter et al. | IEEE | 2015


    Automatic Target Recognition for Passive Radar

    Pisane, Jonathan / Azarian, Sylvain / Lesturgie, Marc et al. | IEEE | 2014