Cortina: Collaborative context-aware indoor positioning employing RSS and RToF techniques

Author

Sun, Zheng ; Farley, Rick ; Kaleas, Telis ; Ellis, Judy ; Chikkappa, Kiran

Author_Institution

Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA

fYear

2011

fDate

21-25 March 2011

Firstpage

340

Lastpage

343

Abstract

Cortina is an energy-efficient indoor localization system, which leverages a wireless sensor network to support navigation and tracking applications. To improve the localization performance, we develop a hybrid ranging system, which incorporate both RSS and RToF-based techniques. To overcome effects from indoor multipath, we design and implement algorithms to take into account various contextual information. We evaluated the system over a 2000m² area instrumented with twenty-six fixed nodes. Evaluation results show the system achieved 2.5m accuracy in a pedestrian tracking application.

Keywords

indoor radio; navigation; wireless sensor networks; Cortina; RSS techniques; RToF techniques; collaborative context-aware indoor positioning; energy-efficient indoor localization system; hybrid ranging system; navigation; pedestrian tracking application; tracking applications; wireless sensor network; Accuracy; Compass; Distance measurement; Floors; Hidden Markov models; Sensors; Wireless sensor networks; Hidden Markov Model; Indoor Localization; Particle Filter; Round-Trip Time-of-Flight;

fLanguage

English

Publisher

ieee

Conference_Titel

Pervasive Computing and Communications Workshops (PERCOM Workshops), 2011 IEEE International Conference on

Conference_Location

Seattle, WA

Print_ISBN

978-1-61284-938-6

Electronic_ISBN

978-1-61284-936-2

Type

conf

DOI

10.1109/PERCOMW.2011.5766901

Filename

5766901