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    Outlier Censoring Based on Sparse Signal Recovery Algorithms

    , M.Sc. Thesis Sharif University of Technology Bassak, Elaheh (Author) ; Karbasi, Mohammad (Supervisor)
    Abstract
    In today’s world, knowledge of the statistical behavior of noise can tremendously affect the accuracy of target detection in radar systems. Therefore, radar systems commonly collect a secondary dataset of homogeneous noise and estimate the statistics of the gathered data, prior to attempting target detection. Specifically, in the case of Gaussian noise with a mean of zero, the entire statistical information of the noise is encoded in its covariance matrix. In practice, however, the challenge is that the training samples do not purely contain homogeneous noise. In fact, some samples contain non-homogeneous outlier signals that do not have the same distribution as the noise samples. In this...