A comprehensive review of metasurface-assisted direction-of-arrival estimation

Abstract

Direction of arrival (DoA) estimation is a key research focus in array signal processing, and numerous progressive direction-finding algorithms have already been developed. In terms of the development of algorithms, metasurfaces can help innovate traditional estimation algorithms as an excellent alternative to phased arrays. New types of artificial intelligence continue to impact traditional algorithms as well as the detection of the incoming wave direction. Miniaturized and integrated incoming wave estimation devices suitable for various systems have become a significant trend in hardware implementation. In this study, the latest progress and trends in this emerging field are reviewed, and their potential value is assessed. First, a brief overview of a combination of classical DoA algorithms and metasurface is presented. Based on this, the applications of common subspace and sparse representation methods were surveyed, followed by a discussion of their potential prospects. The use of artificial intelligence combined with metasurfaces to innovate DoA detection is discussed. Finally, challenges and opportunities for advancing metasurfaces and artificial intelligence in this frontier field are discussed.

Keywords

• direction of arrival estimation
• music and esprit
• classical high-resolution subspace methods
• compressed sensing (cs) algorithms
• machine learning