title: Advanced Pedestrian Positioning System to Smartphones and Smartwatches.
abstract: In recent years, there has been an increasing interest in the development of pedestrian navigation systems for satellite-denied scenarios. The popularization of smartphones and smartwatches is an interesting opportunity for reducing the infrastructure cost of the positioning systems. Nowadays, smartphones include inertial sensors that can be used in pedestrian dead-reckoning (PDR) algorithms for the estimation of the user's position. Both smartphones and smartwatches include WiFi capabilities allowing the computation of the received signal strength (RSS). We develop a new method for the combination of RSS measurements from two different receivers using a Gaussian mixture model. We also analyze the implication of using a WiFi network designed for communication purposes in an indoor positioning system when the designer cannot control the network configuration. In this work, we design a hybrid positioning system that combines inertial measurements, from low-cost inertial sensors embedded in a smartphone, with RSS measurements through an extended Kalman filter. The system has been validated in a real scenario, and results show that our system improves the positioning accuracy of the PDR system thanks to the use of two WiFi receivers. The designed system obtains an accuracy up to 1.4 m in a scenario of 6000 m 2 .
authors.affiliation: Telecommunications and Systems Engineering Department, Universitat Autònoma de Barcelona, Bellaterra 08193, Spain. alejandro.correa@uab.cat.
authors.forename: Alejandro
authors.initials: A
authors.lastname: Correa
authors.affiliation: Institute of Communications and Navigation, German Aerospace Center, Oberpfaffenhofen 82234, Germany. estefania.munoz@dlr.de.
authors.forename: Estefania
authors.initials: E
authors.lastname: Munoz Diaz
authors.affiliation: Institute of Communications and Navigation, German Aerospace Center, Oberpfaffenhofen 82234, Germany. dina.bousdarahmed@dlr.de.
authors.forename: Dina
authors.initials: D
authors.lastname: Bousdar Ahmed
authors.affiliation: Telecommunications and Systems Engineering Department, Universitat Autònoma de Barcelona, Bellaterra 08193, Spain. antoni.morell@uab.cat.
authors.forename: Antoni
authors.initials: A
authors.lastname: Morell
authors.affiliation: Telecommunications and Systems Engineering Department, Universitat Autònoma de Barcelona, Bellaterra 08193, Spain. jose.vicario@uab.cat.
authors.forename: Jose
authors.initials: J
authors.lastname: Lopez Vicario
mesh_terms: D000465:Algorithms; D015374:Biosensing Techniques / Q000379:methods; D006801:Humans; D020407:Internet; D000069636:Pedestrians; D000068997:Smartphone; D016138:Walking / Q000502:physiology
keywords: aiding technology for INS; inertial sensors and systems; received signal strength; smartphone navigation systems; smartwatch