ULA-based near-field source localisation in cognitive femtocell network: a comparative study of genetic algorithm hybridised with pattern search and swarm intelligence

2019 ◽  
Vol 13 (12) ◽  
pp. 1753-1761 ◽  
Author(s):  
Kiran Sultan ◽  
R. A. Alharbey
Keyword(s):  
Genetic Algorithm ◽  
Comparative Study ◽  
Swarm Intelligence ◽  
Near Field ◽  
Pattern Search ◽  
Field Source ◽  
Source Localisation ◽  
Femtocell Network ◽  
Cognitive Femtocell

scholarly journals Spectrum sensing in cognitive femtocell network based on near-field source localisation using genetic algorithm

2017 ◽  
Vol 11 (11) ◽  
pp. 1699-1705 ◽  
Author(s):  
Ayesha Salman ◽  
Ijaz Mansoor Qureshi ◽  
Shahryar Saleem ◽  
Sarah Saeed
Keyword(s):  
Genetic Algorithm ◽  
Spectrum Sensing ◽  
Near Field ◽  
Field Source ◽  
Source Localisation ◽  
Femtocell Network ◽  
Cognitive Femtocell

Bistatic MIMO radar for near field source localisation using PARAFAC

2016 ◽  
Vol 52 (12) ◽  
pp. 1060-1061 ◽  
Author(s):  
P.R. Singh ◽  
Y. Wang ◽  
P. Chargé
Keyword(s):  
Near Field ◽  
Mimo Radar ◽  
Field Source ◽  
Bistatic Mimo Radar ◽  
Source Localisation

Signal reconstruction for near‐field source localisation

2015 ◽  
Vol 9 (3) ◽  
pp. 201-205 ◽  
Author(s):  
Li Jianzhong ◽  
Yide Wang ◽  
Wei Gang
Keyword(s):  
Signal Reconstruction ◽  
Near Field ◽  
Field Source ◽  
Source Localisation

scholarly journals 5D Parameter Estimation of Near-Field Sources Using Hybrid Evolutionary Computational Techniques

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Fawad Zaman ◽  
Ijaz Mansoor Qureshi
Keyword(s):  
Genetic Algorithm ◽  
Interior Point ◽  
Fitness Function ◽  
Near Field ◽  
Pattern Search ◽  
Estimation Accuracy ◽  
Computational Techniques ◽  
Computational Technique ◽  
Interior Point Algorithm ◽  
Validity And Reliability

Hybrid evolutionary computational technique is developed to jointly estimate the amplitude, frequency, range, and 2D direction of arrival (elevation and azimuth angles) of near-field sources impinging on centrosymmetric cross array. Specifically, genetic algorithm is used as a global optimizer, whereas pattern search and interior point algorithms are employed as rapid local search optimizers. For this, a new multiobjective fitness function is constructed, which is the combination of mean square error and correlation between the normalized desired and estimated vectors. The performance of the proposed hybrid scheme is compared not only with the individual responses of genetic algorithm, interior point algorithm, and pattern search, but also with the existing traditional techniques. The proposed schemes produced fairly good results in terms of estimation accuracy, convergence rate, and robustness against noise. A large number of Monte-Carlo simulations are carried out to test out the validity and reliability of each scheme.

scholarly journals 3-D Near Field Source Localization by using Hybrid Genetic Algorithm

2013 ◽  
Vol 6 (23) ◽  
pp. 4464-4469
Author(s):  
Ayesha Khaliq ◽  
Fawad Zaman ◽  
Kiran Sultan ◽  
Ijaz Mansoor Qureshi
Keyword(s):  
Genetic Algorithm ◽  
Source Localization ◽  
Near Field ◽  
Hybrid Genetic Algorithm ◽  
Field Source

Multiple near‐field source localisation with uniform circular array

2013 ◽  
Vol 49 (24) ◽  
pp. 1509-1510 ◽  
Author(s):  
Yuntao Wu ◽  
Hai Wang ◽  
Yanbin Zhang ◽  
Yang Wang
Keyword(s):  
Near Field ◽  
Circular Array ◽  
Field Source ◽  
Source Localisation
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