@inproceedings{19c9521d6d234378afc944b0c6941943,
title = "A Transformer Approach to Two-Dimensional DOA Estimation of Coherent Signals",
abstract = "In this paper, we propose a two-dimensional (2D) direction-of-arrival (DOA) estimation method for coherent signals. This method is based on sparse reconstruction and makes use of the Transformer architecture. An L-shaped uniform-distance array is adopted as the signal-receiving array. We design a two-di-mensional DOA estimation system by integrating the two-dimensional iterative hard-thresholding (IHT) algorithm with the Transformer neural network. Finally, we compare the proposed method with the SS-MUSIC algorithm. Experimental results show that the proposed method can effectively achieve two-dimensional DOA estimation and demonstrates superior performance in low-signal-to-noise ratio (SNR) environments.",
keywords = "2-D DOA estimation, coherent signals, IHT algorithm, sparse re-construction, Transformer",
author = "Suxuan Ye and Yougen Xu and Kun Qian and Xinru Wang",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 5th International Conference on Artificial Intelligence and Industrial Technology Applications, AIITA 2025 ; Conference date: 28-03-2025 Through 30-03-2025",
year = "2025",
doi = "10.1109/AIITA65135.2025.11048093",
language = "English",
series = "2025 5th International Conference on Artificial Intelligence and Industrial Technology Applications, AIITA 2025",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "699--704",
booktitle = "2025 5th International Conference on Artificial Intelligence and Industrial Technology Applications, AIITA 2025",
address = "United States",
}