Antenna Failure Resilience: Deep Learning-Enabled Robust DOA Estimation with Single Snapshot Sparse Arrays

Recent advancements in Deep Learning (DL) for Direction of Arrival (DOA) estimation have highlighted its superiority over traditional methods, offering faster inference, enhanced super-resolution, and robust performance in low Signal-to-Noise Ratio (SNR) environments. Despite these advancements, exi...

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Vydané v:	Conference record - Asilomar Conference on Signals, Systems, & Computers s. 84 - 89
Hlavní autori:	Zheng, Ruxin, Sun, Shunqiao, Liu, Hongshan, Chen, Honglei, Soltanalian, Mojtaba, Li, Jian
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 27.10.2024
Predmet:	Antenna arrays antenna failure Automotive radar Deep learning Direction-of-arrival estimation DOA estimation Estimation Radar Radar antennas Signal resolution Signal to noise ratio single snapshot sparse arrays Superresolution Vehicle dynamics
ISSN:	2576-2303
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