A New Approach for Estimating the Number of Sources Under the Coexistence of Circular and Various Noncircular Sources

Estimation of source number is a fundamental problem of direction-of-arrival (DOA) estimation. In the problem of DOA estimation under the coexistence of circular and various noncircular signals, the source number should be estimated in order to distinguish the signal subspace from the noise subspace. Thus, a new method for source number estimation is proposed in this paper. Using the approach of k-means clustering, the projections of a one-dimensional reduced covariance matrix are divided into two categories. Then the signal subspace and the noise subspace are separated by the optimal classification boundary of those two categories so as to obtain the equivalent source number. Simulation results show that the proposed method has relatively better performance even in low SNR or in a colored noise environment.

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