An Approximate Regularized ML Approach to Censor Outliers in Gaussian Radar Data
This paper considers the problem of censoring outliers from the secondary dataset in a radar scenario where the sample support is limited. To this end, the generalized regularized likelihood function (GRLF) criterion is used and the corresponding regularized maximum likelihood (RML) estimate of the...
Main Authors: | Sudan Han, Luca Pallotta, Vincenzo Carotenuto, Antonio De Maio, Xiaotao Huang |
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Format: | Article |
Language: | English |
Published: |
IEEE
2019-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8718591/ |
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