- Deep Learning|Based Multipath DoAs Estimation Method for ...🔍
- Deep learning|based DOA estimation using CRNN for underwater ...🔍
- Deep Learning Approach in DOA Estimation🔍
- A Novel Tree Model|based DNN to Achieve a High|Resolution DOA ...🔍
- A Deep Learning|Based DoA Estimation Method in Low SNR🔍
- Leveraging Deep Learning for Practical DoA Estimation🔍
- Deep learning based channel estimation method for mine OFDM ...🔍
- Neural network|based DOA estimation for distributed sources in ...🔍
Deep Learning|Based Multipath DoAs Estimation Method for ...
Deep Learning-Based Multipath DoAs Estimation Method for ...
In particular, the DoAs estimation is decomposed into three sub-problems, which are solved by the corresponding convolutional neural network ( ...
Deep Learning-Based Multipath DoAs Estimation Method for ...
The deep CNN-based channel estimation method was introduced for the mmWave massive MIMO systems [22]. A data-driven robust DoA estimation framework integrating.
Deep Learning-Based Multipath DoAs Estimation Method for ...
Download Citation | Deep Learning-Based Multipath DoAs Estimation Method for mmWave Massive MIMO Systems in Low SNR | To realize the direction-of-arrivals ...
Deep learning-based DOA estimation using CRNN for underwater ...
We train the CRNN with multipath signals generated by the BELLHOP model and a uniform line array. Experimental results show that the proposed ...
Deep Learning Approach in DOA Estimation: A Systematic Literature ...
The Pisarenko method is a harmonic analysis method [3]. It obtains the signal subspace and noise subspace by performing eigenvalue decomposition ...
A Novel Tree Model-based DNN to Achieve a High-Resolution DOA ...
Wang, “Deep learning-based multipath DoAs estimation method for mmwave massive MIMO systems in low SNR,” IEEE Trans. Veh. Technol., 2023. [16] X. Wu, X ...
A Deep Learning-Based DoA Estimation Method in Low SNR
This method is realized by constructing the mapping between the covariance matrix and multipath direction-of-angle. The proposed method first constructs a ...
(PDF) Deep Learning-Based DOA Estimation - ResearchGate
However, most existing deep learning-based DOA estimation methods extract DOA information from the covariance matrix (CM) input. In this paper, ...
Leveraging Deep Learning for Practical DoA Estimation - MDPI
This paper presents an experimental validation of deep learning-based direction-of-arrival (DoA) estimation by using realistic data collected via universal ...
Deep learning based channel estimation method for mine OFDM ...
In reference, researchers applied deep learning algorithms to channel estimation in frequency division duplex (FDD) large-scale MIMO-OFDM ...
Neural network-based DOA estimation for distributed sources in ...
To address these challenges, a high-precision autoencoder-regularization dropout-deep convolutional network multilayer classifier (AE-RD-DCNMC)-based DOA ...
Spatial Sectorized Neural Network for 2-D DOA Estimation in the ...
for coherent DOA estimation,” IEEE Signal Process. Lett., vol. 29, pp. 1634–1638, 2022. [15] J. Yu and Y. Wang, “Deep learning-based multipath DoAs estimation.
Direction of arrival estimation in multipath environments using deep ...
The simulation results demonstrate that the proposed DOA estimator enables reliable DOA estimation despite very challenging multipath ...
Online Direction of Arrival Estimation Based on Deep Learning
A supervised learning algorithm for DOA estimation combining convolutional neural network (CNN) and long short term memory (LSTM) is proposed, ...
Improving the Accuracy of Direction of Arrival Estimation with ... - MDPI
Current DOA estimation methods based on deep learning can roughly be divided into two categories. ... Direction of arrival estimation in multipath environments ...
Machine Learning-Based DOA Estimation for Correlated Signals
Current methods intended for DOA estimation purposes show deteriorating performance in these scenarios due to signal correlation, low Signal-to- ...
Multi-DOA estimation based on the KR image tensor and improved ...
Machine learning-based methods are data-driven, they do not rely on prior information about array geometries or signal forms. Researchers have ...
DoA and ToA Estimation Method of OFDM Signal Based on ...
[15] proposed a deep learning-based framework for preamble detection and ToA estimation with high accuracy under multipath and noise interference. [16] ...
An efficient DOA estimation method in multipath environment
Direction of arrival (DOA) estimation of multiple narrowband signals is an important problem in array signal processing including radar, sonar, radio astronomy, ...
Direction-of-Arrival Estimation Using A Machine Learning Framework
... DoA estimation method based on deep neural networks that could achieve better estimation results than the methods based on support vector machine. (SVM).