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Applied Computational Intelligence and Soft Computing
Article . 2022 . Peer-reviewed
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Other literature type . 2022
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Direction of Arrival Estimation for Coherent Signals’ Method Based on LSTM Neural Network

اتجاه تقدير الوصول لطريقة الإشارات المتماسكة بناءً على الشبكة العصبية LSTM
Authors: Hán Trọng Thanh; Nam Ngo Duc; Hưng Trần Văn; Pham Viet Hung;

Direction of Arrival Estimation for Coherent Signals’ Method Based on LSTM Neural Network

Abstract

Radio direction finding system is a system that determines the direction or coordinates of radio signal sources. The main function of this system is to determine the direction of arrival (DOA) of an incident radio wave. DOA information plays an important role in array signal processing and has many applications in communications, radar, seismic survey, etc. In this study, we propose a method to estimate the DOA by using the simulated signal dataset obtained at the linear antenna array (ULA) and the suitable Long Short-Term Memory (LSTM) network model. The performance of the method is evaluated based on the root mean square error (RMSE) parameter and then is compared with 2 other algorithms, multiple signal classification (MUSIC) and deep neural network (DNN) in different cases such as deviation of incoming signals, variation of signal-to-noise ratio (SNR), and coherent incoming signals. The obtained results have shown that the proposed method has significantly improved accuracy compared to other methods.

Keywords

Artificial neural network, Artificial intelligence, Multiscale Seafloor Mapping and Classification Techniques, Direction finding, Antenna (radio), Noise (video), Speech recognition, Oceanography, Antenna array, Pattern recognition (psychology), Image (mathematics), FOS: Mathematics, Speech Enhancement Techniques, Radar, Statistics, Direction of arrival, QA75.5-76.95, FOS: Earth and related environmental sciences, Computer science, Direction-of-Arrival Estimation, Programming language, Earth and Planetary Sciences, Algorithm, Electronic computers. Computer science, SIGNAL (programming language), Signal Processing, Computer Science, Physical Sciences, Telecommunications, Mean squared error, Mathematics, Array Processing for Signal Localization and Estimation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Top 10%
gold