Non-coherent direction of arrival estimation utilizing linear model approximation

Abstract This fast communication presents a non-coherent direction of arrival (DOA) estimation algorithm utilizing the elements squared of the array covariance. Very different from previous non-coherent DOA estimation algorithms, the nonlinear model produced by the squared operation is approximately cast as a linear model, under a high-power reference source. And then, the DOA estimation is efficiently obtained via the mature l 1 -norm minimization. The proposed algorithm can be applied to arbitrary arrays. Focused on the estimation accuracy, the nested coprime array with displaced subarrays (CADiS) is exploited. To resolve the ambiguity problems in the scenario that the sources impinging on the array from the range [ − 90 ∘ , 90 ∘ ] , a simple but effective strategy is introduced. The proposed algorithm performs independent of the phase errors and can provide improved DOA estimation accuracy with reduced computational complexity in large snapshot case. Simulation results demonstrate the effectiveness and superiority of the proposed algorithm.