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Peer-To-Peer UWB Ranges as a Source of Training Data for Estimating BLE RSSI Path-Loss Exponents

This paper presents a practical indoor positioning approach to improve short-range distance estimation using Bluetooth received signal strength (RSSI) and precise ultra-wideband (UWB) range measurement. The conventional distance estimation technique from Bluetooth RSSI uses a classical path loss model that is environment specific. The model faces challenges in determining suitable path loss factors to estimate distance accurately. A curve-fitting function on BLE RSSI values with actual distance shows that the distance estimation error increases with increasing distance. UWB provides a precise range measurement in line of sight (LOS) condition indoors. Therefore, this paper investigates the feasibility of using UWB range as a source of training data for BLE RSSI range estimation. The experimental results show that a line-fitting model of RSSI values using a UWB range gives similar performance compared to the actual distance for short ranges in a complex indoor environment.