High-Resolution Multiple-Source 2D DOA Estimation Using Convolutional Neural Network With Robustness to Array Imperfections
In this paper, we present an efficient convolutional neural network (CNN)-based model to estimate both elevation and azimuth arrival angles of multiple sources with high resolution (small source angular separation). The sources are considered closely spaced in both elevation and azimuth up to 0.5&am...
Saved in:
| Main Authors: | Tarek Sallam, Qun Wang, Ahmed M. Attiya |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10713319/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
TSNetIQ: High-Resolution DOA Estimation of UAVs Using Microphone Arrays
by: Kequan Zhu, et al.
Published: (2025-08-01) -
Dimension-reduction MUSIC for jointly estimating DOA and polarization using plane polarized arrays
by: Wei-jian SI, et al.
Published: (2014-12-01) -
Robust Low-Snapshot DOA Estimation for Sparse Arrays via a Hybrid Convolutional Graph Neural Network
by: Hongliang Zhu, et al.
Published: (2025-07-01) -
Hole-Free Symmetric Complementary Sparse Array Design for High-Precision DOA Estimation
by: He Ma, et al.
Published: (2024-12-01) -
Improved CPD based DOA estimation of nested array
by: Sibei CHENG, et al.
Published: (2021-08-01)