Localization with orientation using RSSI measurements: RF map based approach

Localization of RFIDs in the indoor environment will entail determining both the position and the orientation of the user. This paper develops estimator using RSSI measurements to predict the position and orientation of a transmitter in an indoor environment. The best estimator tried was an K-nearest neighbours model that gave an accuracy of approximately 83% for position prediction and 93% for orientation prediction. It was also found that the RSSI values change throughout the day, meaning that an adaptive estimator is necessary for localization.