Performance Evaluation and Analysis of Direction of Arrival Estimation Using MUSIC, TLS ESPRIT and Pro ESPRIT Algorithms

Source Direction of arrival (DOA) estimation plays an important role in array signal processing, and has a wide range of application.Array signal processing is an important branch in the field of signal processing.In recent years, it has developed dramatically.It can be applied in fields such as radar, communication, sonar, earthquake, exploration, astronomy and biomedicine.Over the past few years, all kinds of algorithms which can be used in DOA estimation have made great achievements, the most classic algorithms among which are Multiple Signal Classification (MUSIC) and Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT).In this paper, we will give an overview on performance of the DOA estimation based on MUSIC as well as ESPRIT (both TLS and Pro ESPRIT) algorithm on uniform linear array (ULA) and in the presence of white noise.We will describe what DOA estimation is, and give a mathematical model of DOA estimation for subspace based DOA methods such as MUSIC, TLS ESPRIT and Pro ESPRIT.Then estimate DOA based on the MUSIC, TLS ESPRIT as well as Pro ESPRIT algorithm, with simulations with MATLAB to simulate factors that affect accuracy and resolution of DOA estimation.The performance of these DOA algorithms for a set of input parameters such as number of snapshots, number of array elements, signal-to-noise ratio, angular separation, element spacing are investigated.