TY - JOUR
T1 - 一种用于矩形阵列的二维波达方向估计方法
AU - Wang, Jianshu
AU - Fan, Yangyu
AU - Du, Rui
AU - Lv, Guoyun
N1 - Publisher Copyright:
© 2019, The Editorial Board of Journal of Xidian University. All right reserved.
PY - 2019/8/20
Y1 - 2019/8/20
N2 - To improve the performance of existing two-dimensional (2-D) grid-less irection of arrival(DOA) estimation methods using the uniform rectangular array(URA) or sparse rectangular array(SRA), a novel 2-D grid-less DOA estimation method based on doubly Toeplitz matrix reconstruction and 2-D ESPRIT is proposed. First, using URA or SRA, the doubly Toeplitz structure of the associated covariance matrix is established. Second, by applying the log-det sparse metric and semi-definite positive constraints, the constrained optimization problem is presented and solved by the majorization-minimization (MM) algorithm. Finally, the azimuth angles and elevation angles are estimated by the 2-D ESPRIT method. The proposed method needs to solve semi-definite programming (SDP) problems repeatedly, which results in a high complexity, while it always provides a superior performance of DOA estimation. In simulations, the proposed method has a very small root-mean-square error (RMSE) in the case of URA and SRA, which can approach the Crammer-Rao bound. Simulation results prove the good performance of the proposed method.
AB - To improve the performance of existing two-dimensional (2-D) grid-less irection of arrival(DOA) estimation methods using the uniform rectangular array(URA) or sparse rectangular array(SRA), a novel 2-D grid-less DOA estimation method based on doubly Toeplitz matrix reconstruction and 2-D ESPRIT is proposed. First, using URA or SRA, the doubly Toeplitz structure of the associated covariance matrix is established. Second, by applying the log-det sparse metric and semi-definite positive constraints, the constrained optimization problem is presented and solved by the majorization-minimization (MM) algorithm. Finally, the azimuth angles and elevation angles are estimated by the 2-D ESPRIT method. The proposed method needs to solve semi-definite programming (SDP) problems repeatedly, which results in a high complexity, while it always provides a superior performance of DOA estimation. In simulations, the proposed method has a very small root-mean-square error (RMSE) in the case of URA and SRA, which can approach the Crammer-Rao bound. Simulation results prove the good performance of the proposed method.
KW - 2-D direction of arrival estimation
KW - Grid-less
KW - Majorization-minimization
KW - Rectangular array
KW - Semi-definite programming
UR - http://www.scopus.com/inward/record.url?scp=85073253335&partnerID=8YFLogxK
U2 - 10.19665/j.issn1001-2400.2019.04.017
DO - 10.19665/j.issn1001-2400.2019.04.017
M3 - 文章
AN - SCOPUS:85073253335
SN - 1001-2400
VL - 46
SP - 122
EP - 129
JO - Xi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University
JF - Xi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University
IS - 4
ER -