User Tracking for Access Control with Bluetooth Low Energy

The Received Signal Strength Indicator (RSSI) of Bluetooth Low Energy (BLE) is a popular means for indoor user localization and tracking as it reflects the transmitter-receiver distance and is readily available in all current smartphones. Since fading, shadowing and antenna patterns cause severe RSSI fluctuations, many RSSI-based localization systems use fingerprinting instead of parameter estimation based on a channel model (e.g. trilateration from distance estimates). Fingerprinting however requires a large effort for training data acquisition and frequent updates in dynamic environments. In this paper we focus on wireless access control with BLE. We demonstrate that a practical implementation of such a tracking system can meet the typical demands of generic access control problems with low- complexity parameter estimation techniques, namely trilateration and optional Kalman filtering. Thereby, satisfactory accuracy is enabled by diversity (averaging in space, time and frequency), calibration and appropriate observation space modeling. We find that including the RSSI directly in the observation space renders trilateration obsolete, which reduces complexity even further.