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In this paper, a novel method based on the entropy estimation of theobservation space eigenvalues is proposed to estimate the number of the sourcesin Gaussian and Non-Gaussian noise. In this method, the eigenvalues ofcorrelation matrix of the observation space will be divided by two sets:eigenvalues of signal subspace and eigenvalues of noise subspace. We will useestimated entropy of eigenvalues to determine the number of sources. In thismethod we do not need any a priory information about signals and noise. Theadvantages of the proposed algorithm based on the performance is compared withthe existing methods in the presence of Gaussian and Non-Gaussian noise. Wehave shown that our proposed method outperforms those methods in theliterature, for different values of observation time and Signal to Noise Ratio,i. e. SNR. It is shown that the algorithm is consistent and also itsprobability of false alarm and probability of missed detection tend to zero forlong observation time.

Source Number Estimation via Entropy Estimation of Eigenvalues (EEE) in Gaussian and Non-Gaussian Noise