LAUSR

In the direction-of-arrival (DOA) estimation with a coprime linear array, the ambiguity problems such as pair matching and grating angle have been investigated. In the ambiguity problem situation, the estimation reliability and accuracy of the existing subarray and adjoined-subarray-based methods degrade due to the low angular resolution. Moreover, it entails excessive computational complexity and execution time. In this paper, to tackle these limitations, DOA estimation is handled as approximating the unknown regression function that maps the eigenvector of signal subspace with the DOA of the incoming source signals using propagator support vector regression. The proposed method offers good generalization and robustness in resolving the ambiguity problem. It achieves full degrees of freedom (DOF) with reduced complexity. To demonstrate the superiority and effectiveness of the proposed method, various simulations in terms of estimation reliability, accuracy, DOF and complexity analysis are provided in comparison with the existing methods.