Sparse representation based two-dimensional direction-of-arrival estimation method with L-shaped array

• Published in: IET radar, sonar & navigation Vol. 10; no. 5; pp. 976 - 982
• Main Authors: Cheng, ZengFei, Zhao, Yongbo, Zhu, YuTang, Shui, Penglang, Li, Hui
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 01.06.2016
• Subjects: 2D direction‐of‐arrival estimation method; 2D DOA estimation method; angle pairing; array signal processing; Arrays; azimuth angle estimation; compound electric angle; compressed sensing; direction‐of‐arrival estimation; Elevation; elevation angles; L‐shaped array; Mathematical models; Navigation; numerical analysis; Representations; Robustness; signal representation; Sonar; sparse recovery problems; sparse representation technique; Two dimensional; compressed sensing; compound electric angle; angle pairing; direction-of-arrival estimation; signal representation; elevation angles; sparse recovery problems; 2D direction-of-arrival estimation method; numerical analysis; 2D DOA estimation method; L-shaped array; azimuth angle estimation; sparse representation technique; array signal processing
• ISSN: 1751-8784; 1751-8792
• DOI: 10.1049/iet-rsn.2014.0547

In this study, a new two-dimensional (2D) direction-of-arrival (DOA) estimation method with L-shaped array is proposed based on the sparse representation framework. The basic idea is to transform the 2D DOA estimation problem into two one-dimensional DOA estimation problems by introducing a new compound electric angle. The compound electric and elevation angles are estimated through solving two sparse recovery problems subsequently. Then the azimuth angle estimation and the angle pairing process are completed simultaneously based on the relationship between the estimated elevation and compound electric angles. Owing to the exploitations of the sparse representation technique and the cross correlation information of the incident signals, the proposed method exhibits a superior performance, including higher angle resolution ability and improved robustness against low signal-to-noise ratio or small number of snapshots, as well as not requiring the knowledge of the source number. Numerical simulations are performed to verify its effectiveness.