Two-Dimensional DOA Estimation Based on Programmable Sparse Metasurface

In this paper, the two-dimensional (2-D) programmable sparse metasurface (PSM) is constructed, and the direction of arrival (DOA) estimation algorithm based on it is proposed. The rows of the programmable metasurface are located with spacings according to a sparse sequence, then the equivalent covariance matrix of an uniform metasurface with more virtual patches is constructed, which improves the estimated number of 2-D DOAs and the DOA estimation accuracy. The simulation results show that the performance of the proposed PSM is almost equal to that of the uniform metasurface with greater number of rows of patches.

I. Introduction

Direction of arrival (DOA) estimation is an important signal processing technique, which has been widely used in many application fields, such as wireless communication, radar and sonar [1]. The two-dimensional (2-D) DOA estimation of signals provides azimuth and elevation DOAs, which plays a crucial role in the signal reconnaissance, positioning, and surveillance [2]–[4]. There is a rule that the more array sensors the greater number of signals to be estimated or higher DOA estimation accuracy can be obtained. But, larger weight and volume usually occur in the traditional sensor array when the number of sensors is greater, which limits the installation platform with limited space, such as unmanned air vehicle, satellite and etc. The invention of the new material metasurface may solve this problem, which has much lighter weight and smaller volume compared to the traditional sensor array [5]–[8].