Parametric Study of Various Direction of Arrival Estimation Techniques

Abstract

The adaptive antenna array system consists of a number of an antenna array element with the signal processing unit, which can adapt its radiation pattern to provide maxima towards the desired user and null towards the interferer. Hence to locate the desired user Direction of Arrival (DOA) of the signal needs to be estimated. This paper presents a parametric study of various DOA estimation algorithms on the uniform linear array (ULA) and also a comparative performance regarding resolution, Signal-to-Noise Ratio (SNR), the number of snapshots, separation angle, etc. It starts with traditional methods of Minimum Variance Distortionless Response (MVDR) algorithm. The subspace-based techniques use the eigenstructure of data covariance matrix. The different subspace-based techniques are Multiple Signal Classification (MUSIC), Root-MUSIC, and Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT). However, simulation results show that the antenna array elements, SNR, the snapshots, coherent nature of signals, and separation angle between the two sources can affect the DOA estimation results. The result shows that MUSIC algorithm has comparatively better resolution than MVDR, Root-MUSIC and ESPRIT algorithms.