Research on Underdetermined DOA Estimation Method with Unknown Number of Sources Based on Improved CNN [PDF]
Sensors, 2023 This paper proposes a joint estimation method for source number and DOA based on an improved convolutional neural network for unknown source number and undetermined DOA estimation.
Fangzheng Zhao +3 more
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Joint Model-Order and Robust DoA Estimation for Underwater Sensor Arrays [PDF]
Sensors, 2023 The direction-of-arrival (DoA) estimation algorithms have a fundamental role in target bearing estimation by sensor array systems. Recently, compressive sensing (CS)-based sparse reconstruction techniques have been investigated for DoA estimation due to ...
Umar Hamid +2 more
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Hierarchical Sectorized ANN Model for DoA Estimation in Smart Textile Wearable Antenna Array Under Strong Noise Conditions [PDF]
SensorsA novel hierarchical sectorized neural network module for a fast direction of arrival (DoA) estimation (HSNN-DoA) of the signal received by a textile wearable antenna array (TWAA) under strong noise conditions is presented.
Zoran Stanković +2 more
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DOA Estimation in B5G/6G: Trends and Challenges [PDF]
Sensors, 2022 Fangqing Wen +2 more
exaly +2 more sources
Two-Stage Fast DOA Estimation Based on Directional Antennas in Conformal Uniform Circular Array
Sensors, 2021 In conformal array radar, due to the directivity of antennas, the responses of the echo signals between different antennas are distinct, and some antennas cannot even receive the target echo signal.
Yao Xie +4 more
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Robust and sparse M-estimation of DOA
Signal Processing, 2023 A robust and sparse Direction of Arrival (DOA) estimator is derived for array data that follows a Complex Elliptically Symmetric (CES) distribution with zero-mean and finite second-order moments. The derivation allows to choose the loss function and four loss functions are discussed in detail: the Gauss loss which is the Maximum-Likelihood (ML) loss ...
Christoph F. Mecklenbräuker +3 more
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Performance analysis of deep neural networks for direction of arrival estimation of multiple sources
IET Signal Processing, 2023 Recently, popular machine learning algorithms have successfully been applied to the direction of arrival (DOA) estimation. An implementation of determination of DOA estimation is presented based on deep neural networks (DNNs) to reduce the computational ...
Min Chen, Xingpeng Mao, Xiuhong Wang
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Deep Unfolded Gridless DOA Estimation Networks Based on Atomic Norm Minimization
Remote Sensing, 2022 Deep unfolded networks have recently been regarded as an essential way to direction of arrival (DOA) estimation due to the fast convergence speed and high interpretability. However, few consider gridless DOA estimation.
Hangui Zhu +4 more
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DoA Estimation via Unlimited Sensing
2020 28th European Signal Processing Conference (EUSIPCO), 2021 Direction-of-arrival (DoA) estimation is a mature topic with decades of history. Despite the progress in the field, very few papers have looked at the problem of DoA estimation with unknown dynamic range. Consider the case of space exploration or near-field and far-field emitters.
Samuel Fernández-Menduiña +3 more
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A novel DOA estimation method for an antenna array under strong interference
EURASIP Journal on Advances in Signal Processing, 2022 Strong interference will affect direction of arrival (DOA) estimation of weak desired signal and even cause DOA estimation failure. This paper investigates the weak signal DOA estimation for an antenna array under strong interference signals, and ...
Ming Zuo, Shuguo Xie
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