Direction-of-Arrival Estimation of Noncircular Signals via Sparse Representation

Abstract

This correspondence addresses the problem of direction-of-arrival (DOA) estimation of noncircular signals, and a new method named noncircular covariance matrix sparse representation (NC-CMSR) is proposed. NC-CMSR realizes DOA estimation by jointly representing the covariance and elliptic covariance matrices of the array output on overcomplete dictionaries subject to sparsity constraint. The new method relies less on the a priori information of the incident signal number than its subspace-based counterparts, and also achieves identification of simultaneous circular and noncircular signals without any extra processes. Simulation results demonstrate the performance of NC-CMSR in DOA estimation and circular-and-noncircular signal identification.