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FMCW radar could detect object's range, speed and Angleof-Arrival, advantagesare robust to bad weather, good range resolution, and good speed resolution. Inthis paper, we consider the FMCW radar as a novel interacting interface onlaptop. We merge sequences of object's range, speed, azimuth information intosingle input, then feed to a convolution neural network to learn spatial andtemporal patterns. Our model achieved 96% accuracy on test set and real-timetest.

Efficient Convolutional Neural Network for FMCW Radar Based Hand Gesture Recognition