Efficient DOA Estimation Method for Reconfigurable Intelligent Surfaces Aided UAV Swarm [PDF]
IEEE Transactions on Signal Processing, 2022 The conventional direction of arrival (DOA) estimation methods are performed with multiple receiving channels. In this paper, a changeling DOA estimation problem is addressed in a different scenario with only one full-functional receiving channel.
Peng Chen +3 more
semanticscholar +1 more source
Efficient Joint DOA and TOA Estimation for Indoor Positioning With 5G Picocell Base Stations [PDF]
IEEE Transactions on Instrumentation and Measurement, 2022 The ubiquity, large bandwidth, and spatial diversity of the fifth-generation (5G) cellular signal render it a promising candidate for accurate positioning in indoor environments where the global navigation satellite system (GNSS) signal is absent.
Mengguan Pan +7 more
semanticscholar +1 more source
Neural-Network-Based DOA Estimation in the Presence of Non-Gaussian Interference [PDF]
IEEE Transactions on Aerospace and Electronic Systems, 2023 This work addresses the problem of direction-of-arrival (DOA) estimation in the presence of non-Gaussian, heavy-tailed, and spatially-colored interference.
S. Feintuch +3 more
semanticscholar +1 more source
A RIS-Based Vehicle DOA Estimation Method With Integrated Sensing and Communication System [PDF]
IEEE transactions on intelligent transportation systems (Print), 2022 With the development of intelligent transportation, growing attention has been received to integrated sensing and communication (ISAC) systems. In this paper, we formulate a novel passive sensing technique to obtain information on the vehicle’s direction
Zhimin Chen +4 more
semanticscholar +1 more source
Reconfigurable Intelligent Surface Aided Sparse DOA Estimation Method With Non-ULA [PDF]
IEEE Signal Processing Letters, 2022 The direction of arrival (DOA) estimation problem is addressed in this letter. A reconfigurable intelligent surface (RIS) aided system for the DOA estimation is proposed. Unlike traditional DOA estimation systems, a low-cost system with only one complete
Peng Chen +3 more
semanticscholar +1 more source
SDOA-Net: An Efficient Deep-Learning-Based DOA Estimation Network for Imperfect Array [PDF]
IEEE Transactions on Instrumentation and Measurement, 2022 The estimation of direction of arrival (DOA) is a crucial issue in conventional radar, wireless communication, and integrated sensing and communication (ISAC) systems.
Peng Chen +4 more
semanticscholar +1 more source
Deep Root Music Algorithm for Data-Driven Doa Estimation
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2023 Direction of arrival (DoA) estimation is a fundamental task in array processing. A popular family of DoA estimation algorithms are subspace methods, which operate by dividing the measurements into distinct signal and noise subspaces.
Dor H. Shmuel +4 more
semanticscholar +1 more source
Gridless DOA Estimation With Multiple Frequencies [PDF]
IEEE Transactions on Signal Processing, 2022 Direction-of-arrival (DOA) estimation is widely applied in acoustic source localization. A multi-frequency model is suitable for characterizing the broadband structure in acoustic signals.
Yifan Wu, M. Wakin, P. Gerstoft
semanticscholar +1 more source
DA-MUSIC: Data-Driven DoA Estimation via Deep Augmented MUSIC Algorithm [PDF]
IEEE Transactions on Vehicular Technology, 2021 Direction of arrival (DoA) estimation of multiple signals is pivotal in sensor array signal processing. A popular multi-signal DoA estimation method is the multiple signal classification (MUSIC) algorithm, which enables high-performance super-resolution ...
J. Merkofer +4 more
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Rank Minimization-Based Toeplitz Reconstruction for DoA Estimation Using Coprime Array [PDF]
IEEE Communications Letters, 2021 In this letter, we address the problem of direction finding using coprime array, which is one of the most preferred sparse array configurations. Motivated by the fact that non-uniform element spacing hinders full utilization of the underlying information
Shengheng Liu +3 more
semanticscholar +1 more source