A Novel Neural Network Method for Direction of Arrival Estimation with Uniform Cylindrical 12-Element Microstrip Patch Array

Date

2008-01-01

Author

Caylar, Selcuk
Dural, Guelbin
Leblebicioğlu, Mehmet Kemal

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

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In this study a new neural network algorithm is proposed for real time multiple source tracking problem with cylindrical patch antenna array based on a previous v reported Modified Neural Multiple Source Tracking Algorithm(MN-MUST). The proposed algorithm, namely Cylindrical Microstrip Patch Array Modified Neural Multiple Source Tracking Algorithm (CMN-MUST) implements W-MUST algorithm on a cylindrical microsttip patch array structure. CMN-MUST algorithm uses the advantage of directive pattern of microstrip patch elements by considering only a part of array elements for a chosen sector. This reduces neural network sizes and also improves the spatial filtering performance. The proposed algorithm improves MN-MUST algorithm in the sense of accuracy and speed while covering the full azimuth range. It is observed that the CMN-MUST algorithm provides an accurate and efficient solution to the target-tracking problem in real time.

Subject Keywords

Antennas, Microstrip, Arrays, Artificial neural networks, Microstrip antenna arrays, Microstrip antennas, Algorithm design and analysis, Antennas and propagation

URI

https://hdl.handle.net/11511/47594

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Department of Electrical and Electronics Engineering, Conference / Seminar