Azimuth and elevation angles estimation using 2-D MUSIC algorithm with an L-shape antenna

Abstract

A noise subspace process, based on the eigenvalue decomposition of an array correlation matrix, which uses an implementation of MUSIC algorithm in two dimensional (2-D) direction of arrival estimation (DOA) problems is proposed. Simulation results are presented, that illustrate the success of the process to determine the correct azimuth and elevation angles of signal wavefronts impinging on a special L-shape antenna array, consisting of two array branches placed on x and y axes.

A survey on the effect of small snapshots number and SNR on the efficiency of the MUSIC algorithm

“…On both cases, the effect appears to obey to an exponential in general. Results for the effect of low values of K and SNR, in the case of the application of the MUSIC algorithm in 2 dimensions [4,5] are going to be shown, also, during the presentation.…”

Two-Dimensional Angles Estimation Method and Its Improved Methods for Single Source With a Sparse Array

“…4(a)-(b), some results can be obtained as: 1) the proposed HRNA method has the lowest elevation and azimuth angles estimation accuracy, while the 2D MUSIC method in [22] gains better elevation and azimuth angles estimation performance than the HRNA one; this is because the 2D MUSIC method directly utilizes the array covariance matrix to achieve the angles estimation, while the HRNA method needs to use the estimated noise varianceσ n to form a new covariance matrix-like so as to complete the elevation and azimuth angles estimation; 2) the JSVD method obtains slightly smaller RMSEs of both elevation and azimuth angles estimates than the 2D MUSIC method, which is consistent with the analysis and results in [19]; 3) the elevation and azimuth angles estimation accuracy of the SI-HRNA method far exceeds the HRNA, 2D MUSIC and JSVD methods, which is because that the SI-HRNA method has much larger array aperture than other three methods; 4) the elevation angle estimation performance of both the HRNA and SI-HRNA methods is nearly equal to their azimuth angle estimation performance, however, the azimuth angle estimation performance of both 2D MUSIC and JSVD methods is slightly below their elevation angle estimation performance; this is because that both the HRNA and SI-HRNA methods first independently obtain the estimates (α r andβ r ) of two independent 2D angles (α r and β r ) using the same computational procedure, and then compute the elevation and azimuth angles by utilizing (5) (in other words, the estimation processes of elevation and azimuth angles are equal and independent with each other), however, the azimuth angle estimates of both 2D MUSIC and JSVD methods are based on their elevation angle ones. show that even at low SNR, the proposed SI-HNRA method is able to complete high accuracy elevation and azimuth angles estimation.…”

“…Figs. 4(a)-(b) and 5(a)-(b) show the RMSEs of angles estimates with D = 5d and D = 16d, respectively, for the proposed methods, JSVD method [19] and 2D MUSIC method [22].…”

“…Since the Joint SVD (JSVD) method in [19] also computes the joint elevation and azimuth angles by first estimating independent angles, thus the proposed methods is compared with both the MUSIC method [18,22] and JSVD method [19]. The proposed methods uses a L-shaped array placed in the X-Y plane, and each LSA branch (see Fig.…”

2-D DOA Estimation for L-Shaped Array With Array Aperture and Snapshots Extension Techniques

“…array elements of the L-shaped array M total should satisfy M total > 2K. Although the maximum identifiable source number of the maximum likelihood (ML) method [11] and the 2D-MUSIC method [26] can overcome this limit, they require multidimensional spectrum peak search, which are too high in computational cost for many real-time applications.…”