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- W4312453218 abstract "The micro-Doppler (MD) signature, an effect that is induced by micro-motion, characterizes the rich motion information of targets, making it a valuable tool for target classification and recognition. However, the MD structure is always destroyed for radar targets with translational motion. In this letter, we propose an end–to–end translational motion compensation network based on a spatial transformer network (STN). First, the effect of the translational motion on the radar echo and its time-frequency graph (TFG) is modeled, so that translational motion compensation is regarded as an image spatial transformation task. Then, a two-branch convolutional network based on residual modules is designed to locate the transformation parameters, and the TFG containing only MD is obtained using a grid generator and sampler. Finally, the simulation results demonstrate that the proposed algorithm has high accuracy and stability." @default.
- W4312453218 created "2023-01-04" @default.
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- W4312453218 date "2022-01-01" @default.
- W4312453218 modified "2023-10-16" @default.
- W4312453218 title "Micro-Doppler Extraction of Radar Targets With Translational Motion Based on Spatial Transformer Network" @default.
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- W4312453218 doi "https://doi.org/10.1109/lsp.2022.3217411" @default.
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