A Novel Neural Network Architecture for Radar Clutter Classification

Date

2020-01-01

Author

Eraslan, Berna
Güvensen, Gökhan Muzaffer
Tanık, Yalçın

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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, potential capabilities of modern radars have become tremendous, with rapid advances in electronics and software technologies. If the radar system processes received echoes based on clutter characteristics, detection performance significantly improves. To classify clutters, neural network structures are studied. A problem specific architecture, specialized in clutter classification, is designed. The design procedure of the neural network is explained with necessary theoretical background information. The performance of the network is illustrated with experimental results.

URI

https://hdl.handle.net/11511/69733

DOI

https://doi.org/10.1109/sami48414.2020.9108755

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

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Citation Formats

B. Eraslan, G. M. Güvensen, and Y. Tanık, “A Novel Neural Network Architecture for Radar Clutter Classification,” 2020, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/69733.