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Our framework consists of four main stages: rough surface modeling, RCS simulation, LFM echo construction, and deep learning–based recognition.
First, we generate random rough surfaces using a Gaussian statistical model to represent complex ground or sea environments.
Next, full-wave electromagnetic simulations are performed in CST to obtain multi-angle radar cross section data for different targets.
Then, based on the simulated RCS and radar signal models, high-fidelity LFM radar echoes are constructed by incorporating Doppler effects.
Finally, these radar echoes are fed into a lightweight one-dimensional convolutional neural network for target recognition.
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IEEE/ICACT20260299 Slide.06
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