Convolution neural network and 77 ​GHz millimeter wave radar based intelligent liquid classification system

An intelligent liquid classification system based on 77 ​GHz ​millimeter wave radar and convolution neural network are proposed in this paper. The data are collected by the AWR1843 radar platform and processed by the neural network on the host PC in real-time. The doppler heatmap generated by radar signal processing is tried for the first time as the input of the system. The information carried by the heatmap in 2 dimensions is analyzed and the reason why the doppler heatmap could be used for classification is explained. The feasible experiment proved that the proposed method can successfully classify 8 kinds of common liquid with high accuracy. The result of the experiment is explained and the limitations of the experiment are discussed. It can be drawn that the combination of FMCW millimeter wave radar and convolution neural network is a method with great potential for liquid classification. The advantages of real time, non-invasive and unilateral measurement can also be used for the detection of dangerous liquids.