  Most smart systems such as smart home and smart health response to human's
locations and activities. However, traditional solutions are either require
wearable sensors or lead to leaking privacy. This work proposes an ambient
radar solution which is a real-time, privacy secure and dark surroundings
resistant system. In this solution, we use a low power, Frequency-Modulated
Continuous Wave (FMCW) radar array to capture the reflected signals and then
construct to 3D image frames. This solution designs $1)$a data preprocessing
mechanism to remove background static reflection, $2)$a signal processing
mechanism to transfer received complex radar signals to a matrix contains
spacial information, and $3)$ a Deep Learning scheme to filter broken frame
which caused by the rough surface of human's body. This solution has been
extensively evaluated in a research area and captures real-time human images
that are recognizable for specific activities. Our results show that the indoor
capturing is clear to be recognized frame by frame compares to camera recorded
video.
