Block Newtonised orthogonal matching pursuit for off‐grid DOA estimation in the presence of unknown mutual coupling

Abstract

Abstract Mutual coupling (MC) between array elements can lead to severe accuracy degradation in direction‐of‐arrival (DOA) estimation. In this study, an off‐grid compressed sensing (CS) approach for DOA estimation in the presence of unknown MC is proposed using block Newtonised orthogonal matching pursuit (NOMP). First, the model of DOA estimation with MC is block sparsely represented to fully utilise the whole array aperture. Then, a block NOMP algorithm with multiple measurement vectors (MMV) is developed to achieve the estimates of DOA, in which the Newton refinement procedure is presented by deriving the first‐ and second‐order derivatives of the block steering matrix with respect to the angle grid. Compared with the subspace‐based and sparse recovery‐based methods with MC, the proposed block NOMP approach has robustness in a small number of snapshots and owns no grid‐mismatch effect. Meanwhile, in comparison to several existing off‐grid DOA estimation methods with MC, it can achieve higher estimation accuracy and similarly low computational complexity. The superior performance of the proposed approach is shown via numerical simulations.

Keywords

• computational complexity
• image representation
• iterative methods
• least squares approximations
• signal representation
• compressed sensing