TY - GEN
T1 - Grid-less two-dimensional DOA estimation methods using uniform or sparse rectangular array
AU - Wang, Jianshu
AU - Fan, Yangyu
AU - Du, Rui
AU - Lv, Guoyun
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/5
Y1 - 2019/5
N2 - Two grid-less two-dimensional (2-D) direction of arrival (DOA) estimation methods using uniform rectangular array (URA) or sparse rectangular array (SRA) are proposed in this paper. Firstly, based on URA or SRA, the doubly Toeplitz structure of the covariance matrix of observed signals is established. Secondly, two reconstruction methods of the doubly Toeplitz matrix are presented, i.e., the least squares (LS) method and the reweighted atomic norm (RAN) methods. At last, the azimuth angles and elevation angles are estimated by the 2-D ESPRIT method efficiently. For simplicity, the two DOA estimation methods are denoted by LS and RAN, respectively. The LS method has lower complexity than recently proposed fast grid-less maximum likelihood (FGML) method, while maintain a similar DOA estimation performance. The RAN method has high complexity, while can achieve superior performance of DOA estimation. Numerical experiments verify the effectiveness and good performance of the proposed methods.
AB - Two grid-less two-dimensional (2-D) direction of arrival (DOA) estimation methods using uniform rectangular array (URA) or sparse rectangular array (SRA) are proposed in this paper. Firstly, based on URA or SRA, the doubly Toeplitz structure of the covariance matrix of observed signals is established. Secondly, two reconstruction methods of the doubly Toeplitz matrix are presented, i.e., the least squares (LS) method and the reweighted atomic norm (RAN) methods. At last, the azimuth angles and elevation angles are estimated by the 2-D ESPRIT method efficiently. For simplicity, the two DOA estimation methods are denoted by LS and RAN, respectively. The LS method has lower complexity than recently proposed fast grid-less maximum likelihood (FGML) method, while maintain a similar DOA estimation performance. The RAN method has high complexity, while can achieve superior performance of DOA estimation. Numerical experiments verify the effectiveness and good performance of the proposed methods.
KW - 2-D direction of arrival estimation
KW - Least squares
KW - Reweighted atomic norm
KW - Uniform or sparse rectangular array
UR - http://www.scopus.com/inward/record.url?scp=85071140447&partnerID=8YFLogxK
U2 - 10.1109/ITAIC.2019.8785862
DO - 10.1109/ITAIC.2019.8785862
M3 - 会议稿件
AN - SCOPUS:85071140447
T3 - Proceedings of 2019 IEEE 8th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2019
SP - 300
EP - 305
BT - Proceedings of 2019 IEEE 8th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2019
A2 - Xu, Bing
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2019
Y2 - 24 May 2019 through 26 May 2019
ER -