Results 21 to 30 of about 31,014 (138)

Blind channel equalization using weighted subspace methods [PDF]

open access: yes, 1999
This paper addresses the problems of blind channel estimation and symbol detection with second order statistics methods from the received data. It can be shown that this problem is similar to direction of arrival (DOA) estimation, where many solutions ...
Cabrera-Bean, Margarita   +1 more
core   +1 more source

Deep Networks for Direction of Arrival Estimation With Sparse Prior in Low SNR

open access: yesIEEE Access, 2023
This work introduces direction of arrival (DOA) estimation considering the sparsity prior in the low signal to noise ratio (SNR) using deep learning (DL).
Yanhua Qin
doaj   +1 more source

Grid-free compressive beamforming [PDF]

open access: yes, 2015
The direction-of-arrival (DOA) estimation problem involves the localization of a few sources from a limited number of observations on an array of sensors, thus it can be formulated as a sparse signal reconstruction problem and solved efficiently with ...
Gerstoft, Peter, Xenaki, Angeliki
core   +2 more sources

Direction of arrival estimation of unknown emitter by deep neural networks with array imperfections

open access: yesIET Radar, Sonar & Navigation, 2023
In array signal processing, high‐resolution direction‐of‐arrival (DOA) estimation by eigendecomposition method requires knowledge of the array covariance matrix and an exact characterisation of the array.
Min Chen, Xingpeng Mao, Libao Liu
doaj   +1 more source

Blind Adaptive Beamforming for a Global Navigation Satellite System Array Receiver Based on Direction Lock Loop

open access: yesRemote Sensing, 2023
The adaptive beamforming algorithm can realize interference suppression and navigation signal enhancement, and has been widely used. However, achieving high-precision real-time estimation of the direction of arrival (DOA) parameters of navigation signals
Jian Wu   +4 more
doaj   +1 more source

Statistically Efficient Methods for Pitch and DOA Estimation [PDF]

open access: yes, 2013
Traditionally, direction-of-arrival (DOA) and pitch estimation of multichannel, periodic sources have been considered as two separate problems. Separate estimation may render the task of resolving sources with similar DOA or pitch impossible, and it may ...
Christensen, Mads Græsbøll   +2 more
core   +2 more sources

Compressive Sensing for High-Resolution Direction-of-Arrival Estimation via Iterative Optimization on Sensing Matrix

open access: yesInternational Journal of Antennas and Propagation, 2015
A novel compressive sensing- (CS-) based direction-of-arrival (DOA) estimation algorithm is proposed to solve the performance degradation of the CS-based DOA estimation in the presence of sensing matrix mismatching. Firstly, a DOA sparse sensing model is
Hongtao Li, Chaoyu Wang, Xiaohua Zhu
doaj   +1 more source

DOA Estimation under GNSS Spoofing Attacks Using a Coprime Array: From a Sparse Reconstruction Viewpoint

open access: yesRemote Sensing, 2022
The antispoofing method using the direction-of-arrival (DOA) feature can effectively improve the application security of the global navigation satellite system (GNSS) receivers.
Yuqing Zhao   +3 more
doaj   +1 more source

A high-resolution DOA estimation method for deep-sea multipath coherent channels [PDF]

open access: yesZhihui kongzhi yu fangzhen
Aiming at the problem of error in deep-sea DOA(Direction of Arrival, DOA) estimation based on plane wave sound field model, this paper establishes the array signal model of deep-sea DOA estimation under multipath channel based on ray theory.
CAO Yongjie, MAO Weining
doaj   +1 more source

Target DoA estimation in passive radar using non-uniform linear arrays and multiple frequency channels [PDF]

open access: yes, 2018
In this paper we present a robust approach for target direction of arrival (DoA) estimation in passive radar that jointly exploits spatial and frequency diversity. Specifically we refer to a DVB-T based passive radar receiver equipped with a linear array
Cardinali, Roberta   +3 more
core   +1 more source

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