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Online ISSN: 0976-8998

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Journal of Networking Technology

Two-Dimensional Direction in The Neural Networks with Radial Basis Function

Marija Agatonovic, Zoran Stankovic, Bratislav Milovanovic, Ivan Milovanovic2 and Nebojsa Doncov
University of Nis Aleksandra Medvedeva 14 18000 Nis, Serbia., Singidunum University Danijelova 29-32 11000 Belgrade, Serbia.,

Abstract: We have used the two-dimensional direction of arrival for calculating the coherent sources with the application of radial basis function. We further used the narrowband signals and rectangular antenna array geometry for network training. The experimental set up and finding is carried out to find the efficiency in the 2D estimation that ultimately help to separate the closely space coherent sources. The RBF neural network paves the way for operating the real-time representation using algorithms.

Keywords: Radial Basis Function (RBF) Neural Network, Rectangular Antenna Array, Coherent Sources, Direction of Arrival Estimation, Two-Dimensional Direction in The Neural Networks with Radial Basis Function

DOI:https://doi.org/10.6025/jnt/2022/13/4/91-98

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References:

[1] Schmidt, R. (1986) Multiple emitter location and signal parameter estimation. IEEE Transactions on Antennas and Propagation, 34, 276–280.
[2] Roy, R. & Kailath, T. (1989) Esprit-estimation of signal parameters via rotational invariance techniques. IEEE Transactions on Acoustics, Speech, and Signal Processing, 37, 984–995 .
[3] Yi, H. & Zhou, X. (2005) “On 2-D Forward-Backward Spatial Smoothing for Azimuth and Elevation Estimation of Coherent Signals,” antennas and propagation society international symposium. In: IEEE, Vol. 2b, pp. 80–83.
[4] Agatonovic, M., Stankovic, Z., Doncov, N., Sit, L., Milovanovic, B. & Zwick, T. (2012) Application of artificial neural networks for efficient high-resolution 2D DOA estimation. Radioengineering, 21, 1178–1186.

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