(Georgia Institute of Technology, 2018-05-01)
Carnes, Joshua T.
This work evaluates the application of Unscented Kalman Filter (UKF) to generate
stochastic localizations of radio frequency identification (RFID) chips in a sensor poor, highly
reflective environment. Localization is done through the application of kNN algorithms and
UKF methods to assign to reference RFID tags. The research is conducted in response to the
needs of NASA for an application on the International Space Station. While the UKF has been
shown to be effective on RFID streams, the sensor poor environment and difficult conditions
aboard the ISS cause a loss of localization. This work shows that a UKF alone is insufficient
for deployment on the ISS and proposes an alternative. Validation methods are proposed, and
initial results are generated. Current industry methods are explored as benchmarks for
algorithm performance.