Abstract: Promoting wireless communication by estimating the direction of arrival of multiple waves incident on the sensor array is a well-known problem in array signal processing. DOA estimation is a widely studied issue in many fields, including wireless communications, astronomical observations, radar, and sonar. One of the main research trends of DOA estimation is to improve the accuracy and super-resolution, and improve the adaptability to harsh scenes such as limited snapshots and low signal-to-noise ratio. Various methods have been proposed to meet these requirements, such as beamformers, subspace-based methods, scarcity induction methods, and maximum likelihood methods. The performance estimated by the DOA has undergone lasting development. In this work, the method based on the MUSIC subspace is used for the estimation of DOA. The subspace-based technique is based on the use of the characteristic structure of the data covariance matrix. The purpose is to analyze the DOA estimation algorithm under low signal-to-noise ratio, array element spacing, number of array elements, and changes in the number of snapshots, signal incidence angle differences, and coherent signals. The performance of the subspace-based DOA estimation algorithm is performed on a 1D linear array. The simulation results show that the influence of different parameters will affect the DOA estimate. The simulation results show that the MUSIC algorithm is accurate in recognizing signals.

Keywords:. DoA, MUSIC,ULA, Antenna

| DOI: 10.17148/IJIREEICE.2021.9807