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

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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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

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Citation Formats

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.