This work revisits the problem of detecting and localizing point sources in a scene using an imaging array and suggests two improvements over traditional approaches. First, the importance of covariance matrix estimation is discussed and several estimators are compared. In particular, the so-called shrinkage estimator is shown to produce better estimates of the covariance matrix and consequently provides improved detection performance over the commonly used naive estimator. We also develop an iterative algorithm for obtaining maximum likelihood estimates of the point source parameters. By using these estimates in forming the detection statistic, further improvements are demonstrated over previously used estimators.


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    Title :

    An Improved GLRT for Image-Based Point Source Detection and Estimation


    Contributors:


    Publication date :

    2017-06-01


    Size :

    798032 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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