Low complexity and high accuracy angle of arrival estimation using eigenvalue decomposition with extension to 2D AOA and power estimation

Saleh O Al-Jazzar,Mahmoud Smadi,Ahmad Al-Nimrat,Artem Muchkaev

doi:10.1186/1687-1499-2011-123

Abstract

In this paper, an angle of arrival (AOA) estimator is presented. Accurate AOA estimation is very crucial for many applications such as wireless positioning and signal enhancement using space processing techniques. The proposed estimator is based upon applying the eigenvalue decomposition (EVD) method on the crosscorrelation matrix of the received signals at two sides of the antenna array doublets. The proposed method is named the eigenvalue-decomposition-based AOA (EDBA) estimator. In comparison with the ESPRIT algorithm, the EDBA has less complexity because the decomposition in the EDBA method is performed only once and on a smaller matrix dimension than that in the ESPRIT algorithm where the decomposition is performed twice. The other advantage is that the EDBA method has better performance than the ESPRIT algorithm. The EDBA is also extended to two-dimensional (2D) AOA estimation with automatic pairing in two ways. The first one performs the 2D AOA estimation by considering the eigenvalues of the crosscorrelation matrix to estimate the azimuth angles and their corresponding eigenvectors to estimate their corresponding elevation angles. Thus, the 2D AOA estimation is performed with automatic pairing and without the need for any pairing or searching techniques. The first 2D extension of the EDBA is named the EDBA-2D estimator. Another 2D AOA estimator that is based upon the EDBA method is also presented and named the Two-EDBA estimator. This second 2D estimator performs the pairing between the azimuth and elevation angles using the alignment of the eigenvalues' magnitudes. An additional advantage for the EDBA estimator is the fact that it provides an estimate for the received signal power paired automatically with its corresponding AOA estimate. Simulations of the proposed EDBA method and its 2D extensions with the signals' power estimation are shown to assess their performance.

Highlights

Many applications require accurate estimation of the angle of arrival (AOA) of the received signal
The azimuth angles are estimated from the eigenvalues of the crosscorrelation matrix, and the elevation angles are estimated from the corresponding eigenvectors of the same crosscorrelation matrix
The eigenvalue-decomposition-based AOA (EDBA) method is applied by taking the eigenvalue decomposition (EVD) of the received signal crosscorrelation matrix

Summary

Introduction

Many applications require accurate estimation of the angle of arrival (AOA) of the received signal. The second advantage of the proposed methods is its better performance in estimating the AOA than that of the ESPRIT algorithm Another benefit for using the EDBA method is its ability to estimate the received signals’ power with automatic pairing with their corresponding AOA estimates. The EDBA-2D method starts by formulating a crosscorrelation matrix from the received signals at both sides of two-parallel ULAs. the azimuth angles are estimated from the eigenvalues of the crosscorrelation matrix, and the elevation angles are estimated from the corresponding eigenvectors of the same crosscorrelation matrix. The second way presented to extend the EDBA method for 2D AOA estimation uses the EDBA method twice and separately at the two ULAs of the L-shaped antenna array to estimate the azimuth and elevation angles.

System model for the EDBA estimator

Simulation results

Conclusion