Ground Radar Target Classification Algorithm Based on Enhanced-Squeeze-and-Excitation-Multiscale Wide Residual Network
2023 International Applied Computational Electromagnetics Society Symposium (ACES-China)（2023）
Abstract
We propose a ground radar target classification algorithm based on the ESE-MWRN. The attention mechanism is introduced to improve the classification performance of the Multiscale Wide Residual Network (MWRN). The algorithm has good classification performance for human, vehicle, and UAV samples, with an overall classification rate as high as 98%.
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Key words
Radar Target Classification,Attention mechanism,Multi-class Classification,Residual Network
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