  Recent research has demonstrated new capabilities in radio frequency (RF)
sensing that apply to health care, smart home, and security applications.
However, previous work in RF sensing requires heavy utilization of the radio
spectrum, for example, transmitting thousands of WiFi packets per second. In
this paper, we present a device-free human sensing system based on received
signal strength (RSS) measurements from a low-cost single carrier narrowband
radio transceiver. We test and validate its performance in three different
applications: real-time heart rate monitoring, gesture recognition, and human
speed estimation. The challenges in these applications stem from the very low
signal-to-noise ratio and the use of a single-dimensional measurement of the
channel. We apply a combination of linear and non-linear filtering, and
time-frequency analysis, and develop new estimators to address the challenges
in the particular applications. Our experimental results indicate that RF
sensing based on single-carrier magnitude measurements performs nearly as well
as the state-of-the-art while utilizing three orders of magnitude less
bandwidth.
