FastGraph Enhanced: high accuracy automatic indoor navigation and mapping - Pendão, Cristiano Gonçalves (2021)
FastGraph is a novel positioning approach recently proposed to address the challenges of positioning in large spaces. Wi-Fi-based indoor positioning solutions often require complex and time-consuming deployments. Fingerprinting, as one of most used approaches, relies on a radio map, usually created by manual site survey, a process unpractical even for small spaces. Moreover, the site survey has to be repeated frequently due to the changes in the radio environment. Wi-Fi-based solutions are also frequently discarded for applications such as indoor vehicle navigation due to limited accuracy. This article introduces FastGraph Enhanced, a new version of FastGraph, able to provide high accuracy positioning, opening new fields of application, such as navigation for autonomous vehicles. In FastGraph Enhanced, the 3D Force-Directed Graph-Based method, used to model the radio environment, is extended with new algorithms, allowing to improve, among other aspects, the positioning performance. The core advantages of FastGraph are maintained, not requiring previous calibration or knowledge about the space. The proposed solution was evaluated in real world, with very significative improvements in positioning accuracy when compared with the basic version of FastGraph (from around 5m to 0.5m), and with state-of-the-art solutions.