@inproceedings{b5641c99c1b44d8f89cb30a2376f154b,
title = "Label Interpolation Based Deep Learning for Direction of Arrival Estimation",
abstract = "In this paper, an end-to-end framework is proposed for direction of arrival (DOA) estimation on the conditions of anechoic and low SNR environments via Deep Learning (DL). Spectrum labels generated by interpolation methods are used for regressors attainment in the training of neural networks. When the regressors converge properly, a peak finding strategy is proposed to estimate DOAs more precisely, which consists of the Gaussian smoothing, rough sampling and Least Squares method. Numerical experiments prove that this framework performs better than the existing DL methods.",
keywords = "DL, DOA estimation, spatial spectral peak search",
author = "Shiwei Ren and Dingsu Xu and Weijiang Wang",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 7th Annual International Conference on Network and Information Systems for Computers, ICNISC 2021 ; Conference date: 23-07-2021 Through 25-07-2021",
year = "2021",
doi = "10.1109/ICNISC54316.2021.00176",
language = "English",
series = "Proceedings - 2021 7th Annual International Conference on Network and Information Systems for Computers, ICNISC 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "937--943",
booktitle = "Proceedings - 2021 7th Annual International Conference on Network and Information Systems for Computers, ICNISC 2021",
address = "United States",
}