RSS Channel-Based Integration for BLE Fingerprinting Positioning.

Fingerprinting using Bluetooth Low Energy (BLE) has emerged as a promising positioning approach due to its technological flexibility and lack of limitations. However, Received Signal Strength (RSS) measurements in BLE exhibit higher variability partly attributed to the protocol’s utilization of different frequency channels within its range. In this study, we leverage frequency information to enhance positioning accuracy. We compare various methods adapted from the existing literature and propose novel approaches. Two distinct BLE RSS databases are employed, including one specifically developed for this research. The results demonstrate that utilizing frequency information can effectively improve positioning accuracy by 10% to 20%, regardless of the selected fingerprinting algorithm. However, the optimal combination method depends on the specific environmental conditions.