TY - GEN
T1 - L-shaped array-based 2-D DOA estimation using parallel factor analysis
AU - Liu, Ding
AU - Liang, Junli
PY - 2010
Y1 - 2010
N2 - For two-dimensional (2-D) directions-of-arrival (DOA) estimation problem, the L-shaped array seems to have higher accuracy than other structured arrays (see [3] for details), and has received much attention. Many algorithms firstly estimate two electric angles separately using the two orthogonal subarrays of the L-shaped array, and then obtain elevation and azimuth angles from these two correctly matched electric angles. However, the failure in pairing will cause severe performance degradation. To avoid the performance degradation resulted from wrong pairing, a parallel factor (PARAFAC) analysis model-based algorithm is proposed in this paper to estimate 2-D DOA in the L-shaped array geometry without pairing parameters. The key points of this paper are: i) Dividing the whole L-shaped array into several subarrays, and constructing several matrices using the second-order statistics of some properly chosen array outputs to alleviate the noise effect and thus improve estimation accuracy; and ii) Forming a PARAFAC analysis model to avoid the performance degradation resulted from wrong pairing. Simulation results are presented to validate the performance of the proposed method.
AB - For two-dimensional (2-D) directions-of-arrival (DOA) estimation problem, the L-shaped array seems to have higher accuracy than other structured arrays (see [3] for details), and has received much attention. Many algorithms firstly estimate two electric angles separately using the two orthogonal subarrays of the L-shaped array, and then obtain elevation and azimuth angles from these two correctly matched electric angles. However, the failure in pairing will cause severe performance degradation. To avoid the performance degradation resulted from wrong pairing, a parallel factor (PARAFAC) analysis model-based algorithm is proposed in this paper to estimate 2-D DOA in the L-shaped array geometry without pairing parameters. The key points of this paper are: i) Dividing the whole L-shaped array into several subarrays, and constructing several matrices using the second-order statistics of some properly chosen array outputs to alleviate the noise effect and thus improve estimation accuracy; and ii) Forming a PARAFAC analysis model to avoid the performance degradation resulted from wrong pairing. Simulation results are presented to validate the performance of the proposed method.
KW - Array signal processing
KW - Directions-of-arrival
UR - http://www.scopus.com/inward/record.url?scp=77958134565&partnerID=8YFLogxK
U2 - 10.1109/WCICA.2010.5554320
DO - 10.1109/WCICA.2010.5554320
M3 - 会议稿件
AN - SCOPUS:77958134565
SN - 9781424467129
T3 - Proceedings of the World Congress on Intelligent Control and Automation (WCICA)
SP - 6949
EP - 6952
BT - 2010 8th World Congress on Intelligent Control and Automation, WCICA 2010
T2 - 2010 8th World Congress on Intelligent Control and Automation, WCICA 2010
Y2 - 7 July 2010 through 9 July 2010
ER -