Passive RFID tomographic imaging for device-free user localization

Localization of users is an important part of location aware systems and smart environments. It forms a major data source for superimposed intention recognition systems. In RF device-free localization (DFL), the person being tracked does not need to wear a RF transmitter or receiver in order to be located. Instead, they are tracked using the changes in signal strength measured on static links in a wireless network. This work presents a new algorithm for RF DFL using passive RFID networks. We formulate and show how a tomographic imaging algorithm provides both low computational complexity and highly accurate position estimates. Using measurements conducted in an indoor environment with various human positions, we find the algorithm can locate the human with as low as 30 cm mean location error.