Performance of ESPRIT and Root-MUSIC for Angle-of-Arrival(AOA) Estimation

Abstract

AOA estimation is used for localization of incident signals such as automotive radar system. [1] There are various methods for estimating the AOA of the signal source. The angle-of-arrival(AOA) estimation algorithms such as MUSIC(MUltiple SIgnal Classification) [2], CBF(conventional beamforming) [3], and capon beamforming [4] require large amounts of computation because they need to search the full range of azimuths. However, ESPRIT [5] and Root-MUSIC [6] have an advantage of low computational complexity because they estimate the AOA analytically without azimuth search. In this paper, we use Monte-Carlo simulation to quantitively get an error in AOA estimation. Our study confirms that Root-MUSIC's performance is better than that of ESPRIT at low SNR(Signal-to-Noise Ratio) condition. When the number of sensors is 4, it is required to use a Root-MUSIC algorithm rather than ESPRIT