Open AccessDOA estimation based on fractional low-order multi-sensor time-frequency analysis in heavy tailed noise
Author(s) -
Jing Xu,
Bin Sun,
Yang Cao,
Hong Wei
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1812/1/012007
Subject(s) - direction of arrival , noise (video) , algorithm , computer science , signal (programming language) , energy (signal processing) , time–frequency analysis , mathematics , statistics , telecommunications , artificial intelligence , radar , antenna (radio) , image (mathematics) , programming language
In order to improve the performance of Direction-of-arrival (DOA) estimation in heavy-tailed noise, a novel DOA estimation method based on fractional low-order multi-sensor time-frequency distribution is proposed. We first use the high-resolution of the fractional low-order multi-sensor time-frequency analysis (FLOM-MTFA) to obtain the time-frequency matrices of the array signal. Then, the high-energy points of the fractional low-order multi-sensor time-frequency matrices is selected to improve the MSNR. We finally compute the averaged FLOM-MTFA matrix and exploit estimation signal parameter via rotational invariance techniques to estimate DOA. Theoretical analysis and simulation results show that the proposed method can effectively estimate DOA in heavy tailed noise.