A Comprehensive Performance Study of Narrowband DOA Estimation Algorithms

In addition to a brief review on narrowband direction of arrival (DOA)estimation, the main purpose of this article is to evaluate and compare the performance of narrowband DOA estimation methods. This paper presents the performance analysis of eight DOA estimation algorithms in three categories, minimum variance distortionless response (MVDR) and delay&sum of classical category, multiple signal classification (MUSIC), Root-MUSIC, estimation of signal parameters via rotational invariance technique (ESPRIT), and minimum norm of subspace-based category, and also deterministic maximum likelihood (DML) and stochastic maximum likelihood (SML) belong to ML category. We present the description and compare the performance, angular accuracy and resolution, of these algorithms for a uniform linear array(ULA),based on three metrics, the root mean square error (RMSE), normalized root mean square error (NRMSE) and the number of detected signal sources. Three cases, single, double and five source signals are simulated in MATLAB software for different signal to noise ratios (SNRs). According to the simulation results, Root-MUSIC, ESPRIT and MUSIC show higher accuracy and resolution than the other algorithms. It should be noted that MUSIC is more applicable because it can be used for different array geometries. Copyright © 2011 Praise Worthy Prize S.r.l. - All rights reserved.