Accurate GSM Indoor Localization

Abstract

Accurate indoor localization has long been an objective of the ubiquitous computing research community, and numerous indoor localization solutions based on 802.11, Bluetooth, ultrasound and infrared technologies have been proposed. This paper presents the first accurate GSM indoor localization system that achieves median within floor accuracy of 4 m in large buildings and is able to identify the floor correctly in up to 60% of the cases and is within 2 floors in up to 98% of the cases in tall multi-floor buildings. We report evaluation results of two case studies conducted over a course of several years, with data collected from 6 buildings in 3 cities across North America. The key idea that makes accurate GSM-based indoor localization possible is the use of wide signalstrength fingerprints. In addition to the 6-strongest cells traditionally used in the GSM standard, the wide fingerprint includes readings from additional cells that are strong enough to be detected, but are too weak to be used for efficient communication. We further show that selecting a subset of highly relevant channels for fingerprinting matching out of all available channels, further improves the localization accuracy.

Discovering routines from large-scale human locations using probabilistic topic models

“…Research using mobile phone data has mostly focused on locationdriven data analysis, more specifically, using Global Positioning System (GPS) data to predict transportation mode [Patterson et al 2003,Reddy et al 2008, to predict user destinations [Krumm and Horvitz 2006] or paths [Akoush and Sameh 2007], and to predict daily step count [Sohn et al 2006]. Other location-driven tasks have made use of Global System for Mobile Communications (GSM) data for indoor localization [Otsason et al 2005] or WiFi for large-scale localization [Letchner et al 2005]. The BeaconPrint algorithm [Hightower et al 2005] uses both WiFi and GSM to learn the places a user goes and detect if the user returns to these places.…”

Coarse In-Building Localization with Smartphones

“…The RADAR system [4] was a building wide tracking system using wireless LAN. The work in [13] relies on the GSM cell towers id and signal strength for indoor localization. The E911 emergency tracking system locates people who call 911 by doing sophisticated radio signaling and computing the time of arrival,and time difference of arrival from cellphone to perform accurate triangulation.…”

“…However, when we enter a building the reception of GPS signals become weak or is lost causing the inability to determine additional location information within the building. Existing solutions for indoor localization include techniques that use WiFi [4], RFID, Bluetooth [2], ultrasound [16], infrared [19] and GSM [17] [13] etc. Many of these solutions rely on external infrastructure or a network of nodes to perform localization.…”

GammaSense: Infrastructureless Positioning Using Background Radioactivity

“…Similar methods were applied to GSM signals by Otsason et al [3]. Unlike RADAR, later systems employed probabilistic models instead of deterministic ones.…”