Results 21 to 30 of about 31,048 (205)
Improved DOA estimation using polarisation diversity : simulations using a wideband propagation model [PDF]
This paper investigates the performance of a number of direction-of-arrival (DOA) estimation algorithms in a wideband macrocellular channel using a dual-polarised antenna array.
AlMidfa, K, Nix, AR, Temeh, EK
core +2 more sources
A Modified Rife Algorithm for Off-Grid DOA Estimation Based on Sparse Representations
In this paper we address the problem of off-grid direction of arrival (DOA) estimation based on sparse representations in the situation of multiple measurement vectors (MMV).
Tao Chen +3 more
doaj +1 more source
A Priori-Based Subarray Selection Algorithm for DOA Estimation
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
Cramer-Rao Bounds for Joint RSS/DoA-Based Primary-User Localization in Cognitive Radio Networks [PDF]
Knowledge about the location of licensed primary-users (PU) could enable several key features in cognitive radio (CR) networks including improved spatio-temporal sensing, intelligent location-aware routing, as well as aiding spectrum policy enforcement ...
Cabric, Danijela +2 more
core +1 more source
In order to solve the problem that the gridless DOA estimation algorithms based on generalized finite rate of innovation (FRI) signal reconstruction model are not suitable for two-dimensional DOA estimation using planar array, a separable gridless DOA ...
Kunda Wang, Lin Shi, Tao Chen
doaj +1 more source
A method of direction-of-arrival (DOA) estimation using array interpolation is proposed in this paper to increase the number of resolvable sources and improve the DOA estimation performance for coprime array configuration with holes in its virtual array.
Aihua Liu +3 more
doaj +1 more source
Direction-of-Arrival Estimation Based on Joint Sparsity
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
Deep Networks for Direction of Arrival Estimation With Sparse Prior in Low SNR
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
Blind channel equalization using weighted subspace methods [PDF]
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
Direction of arrival estimation of unknown emitter by deep neural networks with array imperfections
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

