DOA estimation of rail transit tunnel far field signals based on reconstructive subspace MUSIC

Abstract

For the rail traffic, feasibility of 5th Generation (5G) mobile communication massive Multiple Input Multiple Output (MIMO) used in the tunnel is studying. In order to effectively set up base station, antenna and intelligent reflecting surface (IRS), the direction of arrival (DOA) must be captured. Aiming at the problem of poor performance of two-dimensional MUltiple SIgnal Classification (2D-MUSIC) algorithm in the environment of low signal-to-noise ratio (SNR), small snapshots and small incident angle interval signals, an improved MUSIC algorithm with uniform rectangular array (URA) based on reconstructive subspace is proposed. By reconstructing subspace, a new spatial spectrum is obtained in terms of subspace eigenvectors. Then, the DOAs are obtained by searching the maximum of the new spatial spectrum. High estimation accuracy and angular resolution are often required in practical applications of rail traffic 5G system, and there exist tunnel scenarios that we need the improved MUSIC algorithm has the ability to conduct two-dimensional DOA estimation. Simulations and the measured data of straight tunnel scenario are used to verify the effectiveness of the proposed algorithm and its higher searching precision in complex signal environments such as low SNR, strong-to-weak proximity, and coherent interference.