Radar micro moving gesture recognition method based on multi-scale fusion deep network

Abstract

In order to solve the problem that the micro moving gesture features are not obvious and difficult to be identified, a micro moving gesture recognition method based on multi-scale fusion deep network for millimeter wave radar is proposed in this paper. The method is mainly composed of 2D convolution module, multi-scale fusion module and attention mechanism module. The multi-scale fusion module is composed of three residual blocks of different scales, which can obtain receptive fields of different sizes and obtain multi-scale features. Meanwhile, residual blocks of different scales are fused to increase the diversity of the network and better extract the deep features of the data. The Squeeze-and-congestion (SE) attention mechanism module is added to suppress the channel characteristics with little information. This improves the network identification accuracy and reduces the number of parameters and computation. The experimental results show that this method is simple to implement, doesn't need to do complex data preprocessing. The convergence speed of the network is fast, which can realize the effective recognition of the micro moving gesture.