A Novel for Light-Weighted Indoor Positioning Algorithm with Hybridizing Trilateration and Fingerprinting Method Considering Bluetooth Low Energy Environment

IPS (Indoor Positioning System) has been considered as one of mostly challengeable technical issues at the focus of accuracy and differentiation even though it has been researched long times ago, and many of researches found that fingerprinting approach can show better accuracy comparing with previous trilateration-based schemes. However, regarding huge indoor place, there can be significant calculation problem issue due to a lot of cells to be pre-surveyed radio map and the great number of location anchor point such as beacon device. Furthermore, this can aggregate life time of user handheld devices which would be generally tiny shape and insufficient energy resource. In this paper, we present a new scheme which was researched with a unique goal for improving calculational computing power, with hibridizing traditional trilateration and recently issued fingerprinting approaches under the Bluetooth low energy environment. In addition, we also present experiment results with analytical evaluations to prove the performance of proposed scheme.