A Deep Learning|Based DoA Estimation Method in Low SNR

DoA Estimation based on Deep Learning in Low SNR - IEEE Xplore

A method for estimating the direction-of-arrival (DoA) in low SNR is proposed using a cascaded deep learning. By mapping the covariance matrix to the signal ...

A Deep Learning-Based DoA Estimation Method in Low SNR

A deep learning-based direction-of-angle estimation method is proposed. This method is realized by constructing the mapping between the covariance matrix and ...

Deep Networks for Direction-of-Arrival Estimation in Low SNR

In this work, we consider direction-of-arrival (DoA) estimation in the presence of extreme noise using Deep Learning (DL).

Deep Networks for Direction-of-Arrival Estimation in Low SNR - arXiv

In this work, we consider direction-of-arrival (DoA) estimation in the presence of extreme noise using Deep Learning (DL).

(PDF) Deep Learning-Based DOA Estimation - ResearchGate

... method for DOA estimation in a wide range of SNR. conditions. VII. C ... Deep. networks for direction-of-arrival estimation in low snr,” IEEE.

Deep Networks for Direction-of-Arrival Estimation in Low SNR - arXiv

Therefore, it is considered a grid-based DoA estimation technique. Estimation of signal parameters via rotational invariance techniques.

[PDF] Deep Networks for Direction-of-Arrival Estimation in Low SNR

The ability of the proposed convolutional neural network based supervised learning method for estimating the direction of arrival (DOA) of multiple speakers ...

Deep Networks for Direction-of-Arrival Estimation in Low SNR

In this talk we present a modern approach to DoA estimation based on DL that can overcome some of the challenges and limitations of conventional methods ...

Super resolution DOA estimation based on deep neural network

In this paper, we present a novel DNN framework that realizes higher resolution and better generalization to random signal number and SNR.

Deep Networks for Direction-of-Arrival Estimation in Low SNR

A very recent approach to DoA estimation is via the use of. Deep Learning (DL) [17], [18]. DL-based methods enjoy several advantages over optimization-based ...

Deep Learning Approach in DOA Estimation: A Systematic Literature ...

Compared with traditional algorithms, the DOA estimation algorithm based on deep learning ... DOA estimation performance under low SNR. 5.3.2.

Deep Learning Approach in DOA Estimation: A Systematic Literature ...

timate DOA for signals with unknown signal sources. However, this model does not perform well in an envi-. ronment with a low signal-to-noise ...

Direction-of-Arrival Estimation Method Based on Neural Network ...

At the same time, although the DOA estimation method based on deep learning ... estimation accuracy under the condition of low SNR. 4.5 ...

Data-Driven DOA Estimation Methods Based on Deep Learning for ...

... signal-to-noise ratio (SNR) is low; 2) the accuracy of DOA estimation method based on LSTM-ATT is much higher than that of traditional ...

DOA Estimation Method Based on Improved Deep Convolutional ...

... estimation algorithm under the conditions of low SNR and small snapshot. ... Deep learning-based DOA estimation methods can be divided into two main ...

Deep learning-based DOA estimation using CRNN for underwater ...

In the marine environment, estimating the direction of arrival (DOA) is challenging because of the multipath signals and low signal-to-noise ...

Deep learning based 2D-DOA estimation using L-shaped arrays

Notably, our approach closely approaches the Ziv–Zakai bound (ZZB), particularly in low signal-to-noise ratio (SNR) and low-angle-difference scenarios, even in ...

Deep Learning Approach in DOA Estimation - Wiley Online Library

Machine learning is a process by which machines use ar- tificial neural networks (ANNs) to compute large amounts of. Internet-based data to ...

A gridless DOA estimation algorithm based on unsupervised deep ...

... estimation performance with low SNR and few snapshots is not perfect. Compared with those subspace algorithms, the compressed sensing estimation algorithms ...

LDnADMM-Net: A Denoising Unfolded Deep Neural Network for ...

This paper proposes a novel DOA estimation approach using a deep neural network (DNN) for a NULA in a low SNR.