UCA Root-MUSIC With Sparse Uniform Circular Arrays

Stochastic Framework for Evaluating the Effect of Displaced Antenna Elements on DOA Estimation

“…We now provide a brief summary of the sparse UCA root-MUSIC algorithm [8]. We decompose the component a(θ, ϕ) into phase modes [14], which can be efficiently evaluated as a fast Fourier transform…”

“…The electromagnetic dimensions of the UCA restrict the number of relevant terms in (7) to 2M + 1, i.e., |m| ≤ M , with M ≥ 2π R λ [8]. The weight vector that excites the array with the mth phase mode is given by w…”

“…The random variables describing the position errors are assumed to be multivariate Gaussian distributed and may be correlated. The procedure is illustrated by relying on the Sparse UCA Root-MUSIC [8] DOA estimation algorithm. This method compensates for mutual coupling by incorporating all relevant phase modes of the active elements patterns of the antenna elements in the nominal UCA, even when the number of relevant phase modes is larger than the number of elements.…”

A Novel DOA Estimation Algorithm Using Array Rotation Technique

“…However, in practice, MUSIC algorithm has strict requirements with the placement of array elements, which has a great influence on DOA estimation accuracy, resolution and stability [8]. As a symbolic plane array, the uniform circular array (UCA) can provide both azimuth and elevation information ranging from 0° to 360° and also has other excellent performance such as circular symmetry properties [9][10][11][12][13][14]. Utilizing array manifold directly, the algorithm proposed in [15] could estimate the 2-D DOAs of a single extended signal combining least-squares (LS) method with weighted total LS (WTLS), which leads to a better performance.…”

“…θ ϕ θ ϕ θ ϕ Η Η = P a U U a (10) where MUSIC ( , ) P θ ϕ is expected to show a large positive value if ( , ) θ ϕ is a true DOA, because…”