Results 31 to 40 of about 2,198 (176)

A Priori-Based Subarray Selection Algorithm for DOA Estimation

open access: yesSensors, 2020
A finer direction-of-arrival (DOA) estimation result needs a large and dense array; it may, however, encounter the mutual coupling effect, which degrades the performance of DOA estimation.
Linghao Zeng   +2 more
doaj   +1 more source

Direction-of-Arrival Estimation Based on Joint Sparsity

open access: yesSensors, 2011
We present a DOA estimation algorithm, called Joint-Sparse DOA to address the problem of Direction-of-Arrival (DOA) estimation using sensor arrays. Firstly, DOA estimation is cast as the joint-sparse recovery problem.
Zhitao Huang, Yiyu Zhou, Junhua Wang
doaj   +1 more source

Multisource DOA Estimation in Impulsive Noise Environments Using Convolutional Neural Networks

open access: yesInternational Journal of Antennas and Propagation, 2022
This work proposes an effective high-resolution multisource direction-of-arrival (DOA) estimation method in impulsive noise scenarios based on convolutional neural networks (CNNs). First of all, the array observation matrix is preprocessed and fed into a
Dong Chen, Young Hoon Joo
doaj   +1 more source

Comparison of Direction of Arrival (DOA) Estimation Techniques for Closely Spaced Targets [PDF]

open access: yesInternational Journal of Future Computer and Communication, 2013
This paper deals with different beamforming techniques for DOA estimation. High resolution techniques such as Multiple Signal Classification (MUSIC) and Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) which are subspace based techniques are also discussed. Finally, further resolution improvement is achieved through the use
Nauman Anwar Baig, Mohammad Bilal Malik
openaire   +1 more source

Space-time division cluster DoA estimation algorithm based on UWA spread spectrum signal

open access: yesTongxin xuebao, 2022
To solve the problems of poor stability, low resolution, and performance degradation under low signal-to-noise ratio (SNR) of the direction of arrival (DoA) estimation, a space-time division cluster (STDC) DoA estimation algorithm was proposed for under ...
Feng ZHOU, Baosheng ZHANG, Wenbo ZHANG
doaj   +2 more sources

Research Progress in Methods to Estimate High-resolution Direction of Arrival

open access: yes水下无人系统学报
With the widespread application of array signal processing, the estimation of direction of arrival(DOA) as the core problem of array signal processing has made significant progress.
Wei ZHAO, Xuan LI, Chengpeng HAO
doaj   +1 more source

Application of Sparse Representation to Bartlett Spectra for Improved Direction of Arrival Estimation

open access: yesSensors, 2020
A new technique for high-resolution direction of arrival estimation is presented. The method utilizes the traditional Bartlett spectra and sparse representation to locate emitters in single and multiple emitter scenarios.
Jacob Compaleo, Inder J. Gupta
doaj   +1 more source

FPGA-based real-time implementation for direction-of-arrival estimation

open access: yesThe Journal of Engineering, 2017
Direction-of-arrival (DOA) estimation of radio signals is of utmost importance in many commercial and military applications. In this study, the authors propose an efficient field-programmable gate array (FPGA) architecture for implementing a recently ...
Abdulrahman Alhamed   +6 more
doaj   +1 more source

A Novel Method for DOA and Time Delay Joint Estimation in Multipath OFDM Environment

open access: yesInternational Journal of Antennas and Propagation, 2020
Joint time delay and direction of arrival estimation based on uniform linear arrays in Orthogonal Frequency Division Multiplexing (OFDM) systems has to face the problems posed by coherent multipath environments and high computational complexity.
Xiangzhi Li   +4 more
doaj   +1 more source

Research progress on the depth of anesthesia monitoring based on the electroencephalogram

open access: yesIbrain, Volume 11, Issue 1, Page 32-43, Spring 2025.
Electroencephalogram (EEG) can noninvasive, continuous, and real‐time monitor the state of brain electrical activity, and the monitoring of EEG can reflect changes in the depth of anesthesia (DOA). The development of artificial intelligence can enable anesthesiologists to extract, analyze, and quantify DOA from complex EEG data.
Xiaolan He, Tingting Li, Xiao Wang
wiley   +1 more source

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