@inproceedings{ee464ad38bc14d6e882f35644255cd3a,
title = "Model-Based Deep Learning for Multi-Source 2D-DOA Estimation with Uniform Circular Array",
abstract = "In this paper, a novel two-dimensional direction-of-arrival (2D-DOA) estimator with uniform circular arrays (UCAs) based on model-based deep learning is presented. Inspired by the interpretability of subspace-based methods and improved performance of deep-learning-based methods, a hybrid architecture integrating the feature extraction capability of the deeplearning network with robustness of subspace-based process is proposed. Simulation results demonstrate that the proposed estimator achieves high accuracy and robustness under conditions with low signal-to-noise ratio (SNR) and limited number of snapshots.",
keywords = "2D-DOA estimation, MobileNetV3, UCA-ESPRIT, model-based deep learning, uniform circular array",
author = "Zejun Yang and Qing Shen and Yuzheng Bao",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 2025 IEEE Workshop on Signal Processing Systems, SiPS 2025 ; Conference date: 01-11-2025 Through 04-11-2025",
year = "2025",
doi = "10.1109/SiPS66314.2025.11261298",
language = "English",
series = "2025 IEEE Workshop on Signal Processing Systems, SiPS 2025",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2025 IEEE Workshop on Signal Processing Systems, SiPS 2025",
address = "United States",
}