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Robust Kernel Correlation Based Bi-Channel Signal Detection With Correlated Non-Gaussian Noise
IEEE Signal Processing Letters ( IF 3.9 ) Pub Date : 2021-01-05 , DOI: 10.1109/lsp.2020.3048841 Huadong Lai , Weichao Xu
IEEE Signal Processing Letters ( IF 3.9 ) Pub Date : 2021-01-05 , DOI: 10.1109/lsp.2020.3048841 Huadong Lai , Weichao Xu
This letter proposes a robust detector based on kernel correlation (KC) for detecting the presence of a common random signal shared in two channels corrupted by correlated non-Gaussian impulsive noise. A bivariate Gaussian mixture (GM) distribution is employed to simulate the correlation and impulsive characteristic of the noise across two channels. The test statistic is constructed by the dot product of preprocessed data obtained by imposing the nonlinear Gaussian kernel on the original observed samples from the two channels. Performance metrics with respect to the probabilities of false alarm and detection are established in view of the central limit theorem (CLT). Simulation results illustrated that, in terms of receiver operating characteristic (ROC) curve and detection probability, the proposed method is superior to other state-of-the-art detection algorithms in the literature.
更新日期：2021-02-02
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