Model-Based Localization and Tracking Using Bluetooth Low-Energy Beacons

Creative Commons License

Danis F. S., CEMGİL A. T.

SENSORS, vol.17, no.11, 2017 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 17 Issue: 11
  • Publication Date: 2017
  • Doi Number: 10.3390/s17112484
  • Journal Name: SENSORS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Keywords: Bluetooth low-energy localization, hidden Markov model, BLE tracking, observation probability estimation, Wasserstein distance, Wasserstein interpolation, affine Wasserstein combination, sequential Monte Carlo, INDOOR TRACKING, FUSION, WIFI
  • Galatasaray University Affiliated: Yes

Abstract

We introduce a high precision localization and tracking method that makes use of cheap Bluetooth low-energy (BLE) beacons only. We track the position of a moving sensor by integrating highly unreliable and noisy BLE observations streaming from multiple locations. A novel aspect of our approach is the development of an observation model, specifically tailored for received signal strength indicator (RSSI) fingerprints: a combination based on the optimal transport model of Wasserstein distance. The tracking results of the entire system are compared with alternative baseline estimation methods, such as nearest neighboring fingerprints and an artificial neural network. Our results show that highly accurate estimation from noisy Bluetooth data is practically feasible with an observation model based on Wasserstein distance interpolation combined with the sequential Monte Carlo (SMC) method for tracking.