Resolving manifold ambiguities for direction-of-arrival estimation of sparse array using semi-circular substrates

Sparse linear array has some advantages over uniform linear array in some applications. However, it is well known that sparse array always suffers from manifold ambiguity, which has significant influence on direction-of-arrival (DOA) estimation and resolution. In this study, a new method based on the multiple signal classification (MUSIC) for resolving manifold ambiguities of uncorrelated sources by using semi-circular substrate is proposed for DOA estimation of sparse array. Spurious MUSIC peak spectrums are generated because of a linear combination of the steering vectors of true DOAs. The main idea of the proposed method is to setup one or several semi-circular medium substrates at the front of some elements. The phases of these elements are changed through the refractive index and the radii of those semi-circular substrates. This treatment breaks down the previous linearity of the steering vectors for the array without adding the substrates. Thus, true DOA peaks can be discriminated according to this feature. Simulation results show good performance of the proposed method. Trivial and nontrivial ambiguities are efficiently resolved. © The Institution of Engineering and Technology 2013.