Analysis of Bluetooth Indoor Localization Technologies and Experiemnt of Correlation between RSSI and Distance

Abstract

In this paper, we present indoor localization technologies using the bluetooth signal categorizing them into proximity based, triangulation based and fingerprinting based technologies. Then we provide localization accuracy improvement algorithms such as moving average, K-means, particle filter, and K-Nearest neighbor algorithms. We define important performance issues for indoor localization technologies and analyze recent technologies according to the performance issues. Finally we provide experimental results for correlation between RSSI and distance. We believe that this paper provide wise view and necessary information for recent localization technologies using the bluetooth signal.

Research on Indoor AGV Fusion Localization Based on Adaptive Weight EKF Using Multi-sensor

“…[2] The latter provides positioning for the car by measuring environmental factors or external data, combined with the actual positioning model. A typical one is based on RSSI (Received Signal Strength Indication) to achieve positioning, and the signal can be in the form of Wi-Fi [3], Bluetooth [4], UWB [5], etc. According to the attenuation characteristics of electromagnetic waves in space, the relative position between the device and the base station can be calculated from the negative correlation between the distance and signal strength of the device and the base station.…”