An inhomogeneity suppression constant false alarm rate detector (IS-CFAR) based on statistical modeling is proposed for inhomogeneous sonar or radar data. First, the inhomogeneous background is modeled and classified based on ordered statistics. Then, the background power is estimated based on the different group of data according to the model of the inhomogeneous background. Finally, the IS-CFAR is designed to improve the detection performance for inhomogeneous sonar or radar data. Simulation results show that the IS-CFAR detector can suppress the background inhomogeneity and improve the CFAR detection performance under inhomogeneous background.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Inhomogeneity Suppression CFAR Detection Based on Statistical Modeling


    Contributors:
    He, Xinbiao (author) / Xu, Yanwei (author) / Liu, Minggang (author) / Hao, Chengpeng (author)


    Publication date :

    2023-04-01


    Size :

    3404152 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    DL-CFAR: A Novel CFAR Target Detection Method Based on Deep Learning

    Lin, Chia-Hung / Lin, Yu-Chien / Bai, Yue et al. | IEEE | 2019


    Adaptive array CFAR detection

    Kalson, S.Z. | IEEE | 1995


    Decentralized CFAR signal detection

    Barkat, M. / Varshney, P.K. | IEEE | 1989


    Adaptive Array CFAR Detection

    Kalson, S.Z. | Online Contents | 1995