Underdetermined DOA Estimation Using Unfold Coprime Array From the Perspective of Sum-Difference Co-Array

Abstract

Direction-of-Arrival (DOA) estimation with sparse non-uniform linear arrays (SNLAs) has recently attracted a growing concern for the reason that more sources than the number of physical sensors can be resolved as compared with the conventional uniform linear arrays (ULAs). In this paper, we develop an underdetermined DOA estimation method using unfold coprime array (unfold CPA) from the perspective of sum-difference co-array (SDCA). By jointly using the temporal and spatial information of the impinging sources and the Khatri-Rao (KR) product operation, the SDCA of the unfold CPA are obtained, which can provide more consecutive DOF and larger array aperture than the SNLAs based on the difference co-array (DCA). Additionally, benefitting from the array configuration of the unfold CPA, the weight functions of the physical sensor pairs with small separations are equal to zero, thus the mutual coupling effects between sensors are reduced significantly. The theoretical propositions and numerical simulations are provided to confirm the effectiveness and superior performance of the proposed method.