Human Activity Recognition Based on Frequency-Modulated Continuous Wave and DenseNet

With the development of wireless technology, Frequency-Modulated Continuous Wave (FMCW) radar has increased sensing capability and can be used to recognize human activity. These applications have gained wide-spread attention become a hot research area. FMCW signals reflected by target activity collected, recognized based on measurements. This paper focused recognition DenseNet. We collected point clouds from analyzed them because different activities could lead unique cloud features. built trained neural network implement using signal. Firstly, this presented recent reviews about signals. Then, it introduced basic concepts described fundamental principles system radar. also provided framework, experiment scenario, DenseNet structure. Finally, we experimental results accuracy models. The achieved 100 percent for five concluded discussing current issues future directions.