Deep Learning Using Synthesized Data for Communications and Radar
This white paper demonstrates how you can use MATLAB® for modulation identification and target classification in radar and communications applications. Three application examples are presented that demonstrate possible workflows. The first two examples use deep learning to identify waveform modulation types. The third example uses radar returns to identify objects based on radar cross section(RCS) and motion characteristics.The examples show how you can synthesize communications and radar baseband waveforms and radar reflections off objects using Phased Array System Toolbox™ and Communications Toolbox™ and configure, train, and implement learning networks using Deep Learning Toolbox™ and Statistics and Machine Learning Toolbox™.
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