TY - GEN
T1 - Application of Steering Vectors Rotation Invariance in DOA Estimation with Mutual Coupling
AU - Song, Zhen
AU - Yu, Changjun
AU - Liu, Aijun
AU - Wang, Linwei
AU - Shao, Shuai
AU - Li, Hongbo
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - The mutual coupling phenomenon between the array elements adversely affects the mutual position estimation in a uniform linear array (ULA). Inspired by the idea of ESPRIT, a novel direction of arrival (DOA) estimation algorithm based on the rotation invariance of the modified steering vectors is proposed to estimate DOAs under mutual coupling error by blind signal separation (BSS). The algorithm denoise at the beginning with the help of the signal subspace. To estimate the modified steering vector, a BSS algorithm named Joint Approximate Diagonalization of Eigenmatrices (JADE) is presented. Finally, the rotation invariance between particular elements of the modified steering vector can be used to estimate the DOAs. The proposed algorithm only needs to solve several one-variable equations to obtain the DOA estimates, which reduces the amount of calculation. The simulation results show that the algorithm can obtain more accurate estimates under the condition of low SNR.
AB - The mutual coupling phenomenon between the array elements adversely affects the mutual position estimation in a uniform linear array (ULA). Inspired by the idea of ESPRIT, a novel direction of arrival (DOA) estimation algorithm based on the rotation invariance of the modified steering vectors is proposed to estimate DOAs under mutual coupling error by blind signal separation (BSS). The algorithm denoise at the beginning with the help of the signal subspace. To estimate the modified steering vector, a BSS algorithm named Joint Approximate Diagonalization of Eigenmatrices (JADE) is presented. Finally, the rotation invariance between particular elements of the modified steering vector can be used to estimate the DOAs. The proposed algorithm only needs to solve several one-variable equations to obtain the DOA estimates, which reduces the amount of calculation. The simulation results show that the algorithm can obtain more accurate estimates under the condition of low SNR.
KW - blind signal separation
KW - direction of arrival
KW - mutual coupling
KW - rotation invariance
UR - https://www.scopus.com/pages/publications/85181141972
U2 - 10.1109/Radar53847.2021.10028024
DO - 10.1109/Radar53847.2021.10028024
M3 - 会议稿件
AN - SCOPUS:85181141972
T3 - Proceedings of the IEEE Radar Conference
SP - 1571
EP - 1576
BT - 2021 CIE International Conference on Radar, Radar 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 CIE International Conference on Radar, Radar 2021
Y2 - 15 December 2021 through 19 December 2021
ER -