Radar-based hand gesture recognition using I-Q echo plot and convolutional neural network

The present paper proposes a technique for the automatic recognition of hand gestures using a 2.4-GHz continuous radar and a convolutional neural network. The proposed technique applies the neural network to the time-domain I-Q plot of radar echoes. The accurate recognition capability of the technique was established with a set of radar data for three types of hand gesture performed by a participant. The radar echo trajectories were converted to low-resolution images to achieve fast signal processing, and the neural network was trained using the images. Another set of I-Q plot images were used for the evaluation of the recognition accuracy. The results indicate that the proposed technique is able to recognize hand gestures with accuracy exceeding 90%.