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Range and Direction of Arrival Estimation of Near-Field Sources in Sensor Arrays using Differential Evolution Algorithm

by Yawar Ali Sheikh, Rizwan Ullah, Zhongfu Ye
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 139 - Number 4
Year of Publication: 2016
Authors: Yawar Ali Sheikh, Rizwan Ullah, Zhongfu Ye
10.5120/ijca2016909141

Yawar Ali Sheikh, Rizwan Ullah, Zhongfu Ye . Range and Direction of Arrival Estimation of Near-Field Sources in Sensor Arrays using Differential Evolution Algorithm. International Journal of Computer Applications. 139, 4 ( April 2016), 16-20. DOI=10.5120/ijca2016909141

@article{ 10.5120/ijca2016909141,
author = { Yawar Ali Sheikh, Rizwan Ullah, Zhongfu Ye },
title = { Range and Direction of Arrival Estimation of Near-Field Sources in Sensor Arrays using Differential Evolution Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { April 2016 },
volume = { 139 },
number = { 4 },
month = { April },
year = { 2016 },
issn = { 0975-8887 },
pages = { 16-20 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume139/number4/24478-2016909141/ },
doi = { 10.5120/ijca2016909141 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:40:02.681974+05:30
%A Yawar Ali Sheikh
%A Rizwan Ullah
%A Zhongfu Ye
%T Range and Direction of Arrival Estimation of Near-Field Sources in Sensor Arrays using Differential Evolution Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 139
%N 4
%P 16-20
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Many algorithms have been proposed in recent years for source localization in near field. Some are based on subspace methods and some use evolutionary computing techniques. This article presents the performance of Differential Evolution (DE) algorithm for range and DOA estimation of near field narrow band sources, impinging on a uniform linear array (ULA) of passive sensors. Mean square error (MSE) is used as a fitness function because it requires only a single snapshot to converge and perform better even in negative SNR. The main contribution of this work is to explore the effectiveness of DE without hybridization for uniform linear arrays. The results of DE are compared with the results of Genetic Algorithm (GA). The effectiveness of both the algorithms is tested on the basis of a large number of Monte-Carlo simulations and their statistical analysis.

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Index Terms

Computer Science
Information Sciences

Keywords

Differential Evolution Direction of Arrival Evolutionary Computing Near field Source Localization.

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