A novel ULA-based geometry for improving AOA estimation

Shahriar Shirvani-Moghaddam,Farida Akbari

doi:10.1186/1687-6180-2011-39

Abstract

Due to relatively simple implementation, Uniform Linear Array (ULA) is a popular geometry for array signal processing. Despite this advantage, it does not have a uniform performance in all directions and Angle of Arrival (AOA) estimation performance degrades considerably in the angles close to endfire. In this article, a new configuration is proposed which can solve this problem. Proposed Array (PA) configuration adds two elements to the ULA in top and bottom of the array axis. By extending signal model of the ULA to the new proposed ULA-based array, AOA estimation performance has been compared in terms of angular accuracy and resolution threshold through two well-known AOA estimation algorithms, MUSIC and MVDR. In both algorithms, Root Mean Square Error (RMSE) of the detected angles descends as the input Signal to Noise Ratio (SNR) increases. Simulation results show that the proposed array geometry introduces uniform accurate performance and higher resolution in middle angles as well as border ones. The PA also presents less RMSE than the ULA in endfire directions. Therefore, the proposed array offers better performance for the border angles with almost the same array size and simplicity in both MUSIC and MVDR algorithms with respect to the conventional ULA. In addition, AOA estimation performance of the PA geometry is compared with two well-known 2D-array geometries: L-shape and V-shape, and acceptable results are obtained with equivalent or lower complexity.

Highlights

Signal processing using an array of sensors provide more capability than a single sensor through analysis of wavefields [1]
Different methods have been suggested to enhance the performance of available algorithms including increasing the accuracy and resolution of Angle of Arrival (AOA) estimation algorithms
New Uniform Linear Array (ULA)-based array geometry is proposed and presented which can remove this drawback by keeping the simplicity in implementation and analysis

Summary

Introduction

Signal processing using an array of sensors provide more capability than a single sensor through analysis of wavefields [1]. The accuracy and resolution threshold of two well-known AOA estimation algorithms, MUltiple SIgnal Classification (MUSIC) and Minimum Variance Distortionless Response (MVDR), are compared to evaluate the performance of the simple ULA, PA, L-shape and V-shape arrays. These results include the effect of number of data snapshots, effect of different SNRs considering boresight and endfire directions and comparison of the array configurations (ULA, PA, L-shape and V-shape arrays) in AOA estimation performance, estimation accuracy as well as resolution, and their computational complexity.

Results

Conclusion