Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
A neural network method for direction of arrival estimation with uniform circular dipole array in the presence of mutual coupling
Date
2007-06-16
Author
Caylar, Selcuk
Leblebicioğlu, Mehmet Kemal
Dural, Guelbin
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
226
views
0
downloads
Cite This
In recent years application of Neural Network (NN) algorithms in both target tracking problem and DoA estimation have become popular because of the increased computational efficiency This paper presents the implementation of modified neural network algorithm(MN-MUST) to the uniform circular dipole array in the presence of mutual coupling. In smart antenna systems, mutual coupling between elements can significantly degrade the processing algorithms. In this paper mutual coupling affects on MN-MUST has been investigated. MN-MUST algorithm applied to the Uniform Circular Array (UCA) geometry for first time. The validity of MN-MUST algorithm in the presence of mutual coupling has been proved for UCA. Simulation results of MN-MUST algorithm are provided for UCA. The presence of mutual coupling degraded the MN-MUST algorithm performed in the absence of mutual coupling, as expected.
Subject Keywords
Remote sensing
,
Engineering
URI
https://hdl.handle.net/11511/37484
DOI
https://doi.org/10.1109/rast.2007.4284050
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
A Meta-Heuristic Paradigm for solving the Forward Kinematics of 6-6 General Parallel Manipulator
Chandra, Rohitash; Frean, Marcus; Rolland, Luc (2009-12-18)
The forward kinematics of the general Gough platform, namely the 6-6 parallel manipulator is solved using hybrid meta-heuristic techniques in which the simulated annealing algorithm replaces the mutation operator in a genetic algorithm. The results are compared with the standard simulated annealing and genetic algorithm. It shows that the standard simulated annealing algorithm outperforms standard genetic algorithm in terms of computation time and overall accuracy of the solution on this problem. However, t...
A hybrid genetic algorithm for the discrete time-cost trade-off problem
Sönmez, Rifat (2012-10-01)
In this paper we present a hybrid strategy developed using genetic algorithms (GAs), simulated annealing (SA), and quantum simulated annealing techniques (QSA) for the discrete time-cost trade-off problem (DTCTP). In the hybrid algorithm (HA), SA is used to improve hill-climbing ability of GA. In addition to SA, the hybrid strategy includes QSA to achieve enhanced local search capability. The HA and a sole GA have been coded in Visual C++ on a personal computer. Ten benchmark test problems with a range of 1...
A new neural network approach to the target tracking problem with smart structure
Caylar, Selcuk; Leblebicioğlu, Mehmet Kemal; Dural, Gülbin (2006-12-01)
The algorithm presented in this paper, namely the modified neural multiple source tracking algorithm (MN-MUST) is the modified form of the recently published work, a NN algorithm, the neural multiple-source tracking (N-MUST) algorithm, was presented for locating and tracking angles of arrival from multiple sources. MN-MUST algorithm consists of three stages that are classified as the detection, filtering and DoA estimation stages. In the first stage a number of radial basis function neural networks (RBFNN) ...
A low-power robust humidity sensor in a standard CMOS process
Okcan, Burak; Akın, Tayfun (2007-11-01)
This paper presents a low-cost thermal-conductivity-based humidity sensor implemented using a 0.6-mu m CMOS process, where suspended p-n junction diodes are used as the humidity-sensitive elements. The measurement method uses the difference between the thermal conductivities of air and water vapor at high temperatures by comparing the output voltages of two hea ted and thermally isolated diodes; one of which is exposed to the environment and has a humidity-dependent thermal conductance, while the other is s...
A nested iterative scheme for computation of incompressible flows in long domains
Manguoğlu, Murat; Tezduyar, Tayfun E.; Sathe, Sunil (Springer Science and Business Media LLC, 2008-12-01)
We present an effective preconditioning technique for solving the nonsymmetric linear systems encountered in computation of incompressible flows in long domains. The application category we focus on is arterial fluid mechanics. These linear systems are solved using a nested iterative scheme with an outer Richardson scheme and an inner iteration that is handled via a Krylov subspace method. Test computations that demonstrate the robustness of our nested scheme are presented.
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
S. Caylar, M. K. Leblebicioğlu, and G. Dural, “A neural network method for direction of arrival estimation with uniform circular dipole array in the presence of mutual coupling,” 2007, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/37484.