This paper deals with the estimation of the clutter covariance matrix in airborne radar space-time adaptive processing (STAP). Based on the persymmetry property, a novel STAP method, referred to as persymmetric extended factored processing (Per-EFA), is derived, which can make a more intensive use of the secondary data and improve the STAP performance in training-limited scenarios. Simulation results demonstrate the effectiveness of this method.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Improving EFA-STAP performance using persymmetric covariance matrix estimation


    Contributors:
    Yalong Tong (author) / Tong Wang (author) / Jianxin Wu (author)


    Publication date :

    2015-04-01


    Size :

    2434684 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English