See through walls with Wi-Fi

Abstract

Wi-Fi signals are typically information carriers between a transmitter and a receiver. In this thesis, we show that Wi-Fi can also extend our senses, enabling us to see moving objects through walls and behind closed doors. For example, we can identify the number of people in a closed room and their relative locations. We can also identify simple gestures made behind a wall. Further, by combining a sequence of gestures, a human can communicate messages to a wireless receiver without carrying any transmitting device. The thesis introduces two main innovations. First, it shows how one can use MIMO interference nulling to eliminate reflections off static objects and focus the receiver on a moving target. Second, it shows how one can track a human by treating the motion of a human body as an antenna array and tracking the resulting RF beam. We demonstrate the validity of our design by building it into USRP software radios and testing it in office buildings.