Human Mobility Enhances Global Positioning Accuracy for Mobile Phone Localization

Global positioning system (GPS) has enabled a number of geographical applications over many years. Quite a lot of location-based services, however, still suffer from considerable positioning errors of GPS (usually 1 to 20 m in practice). In this study, we design and implement a high-accuracy global positioning solution based on GPS and human mobility captured by mobile phones. Our key observation is that smartphone-enabled dead reckoning supports accurate but local coordinates of users' trajectories, while GPS provides global but inconsistent coordinates. Considering them simultaneously, we devise techniques to refine the global positioning results by fitting the global positions to the structure of locally measured ones, so the refined positioning results are more likely to elicit the ground truth. We develop a prototype system, named GloCal, and conduct comprehensive experiments in both crowded urban and spacious suburban areas. The evaluation results show that GloCal can achieve 30 percent improvement on average error with respect to GPS. GloCal uses merely mobile phones and requires no infrastructure or additional reference information. As an effective and light-weight augmentation to global positioning, GloCal holds promise in real-world feasibility.

[1]  Yunhao Liu,et al.  Locating in fingerprint space: wireless indoor localization with little human intervention , 2012, Mobicom '12.

[2]  John Krumm,et al.  Accuracy characterization for metropolitan-scale Wi-Fi localization , 2005, MobiSys '05.

[3]  C. A. HART,et al.  Manual of Photogrammetry , 1947, Nature.

[4]  Guobin Shen,et al.  Walkie-Markie: Indoor Pathway Mapping Made Easy , 2013, NSDI.

[5]  Mohamed N. El-Derini,et al.  GAC: Energy-Efficient Hybrid GPS-Accelerometer-Compass GSM Localization , 2010, 2010 IEEE Global Telecommunications Conference GLOBECOM 2010.

[6]  Bernhard Hofmann-Wellenhof,et al.  GNSS - Global Navigation Satellite Systems: GPS, GLONASS, Galileo, and more , 2007 .

[7]  Michael J. Rycroft,et al.  Understanding GPS. Principles and Applications , 1997 .

[8]  Bo Zhang,et al.  Differential Coherent Algorithm Based on Fast Navigation-Bit Correction for Airborne GNSS-R Software Receivers , 2013 .

[9]  Charles F. F. Karney Transverse Mercator with an accuracy of a few nanometers , 2010, 1002.1417.

[10]  Song Han,et al.  WheelLoc: Enabling continuous location service on mobile phone for outdoor scenarios , 2013, 2013 Proceedings IEEE INFOCOM.

[11]  Bradford W. Parkinson,et al.  Global positioning system : theory and applications , 1996 .

[12]  Anshul Rai,et al.  Zee: zero-effort crowdsourcing for indoor localization , 2012, Mobicom '12.

[13]  Robert Harle,et al.  Pedestrian localisation for indoor environments , 2008, UbiComp.

[14]  Berthold K. P. Horn,et al.  Closed-form solution of absolute orientation using unit quaternions , 1987 .

[15]  Injong Rhee,et al.  Towards Mobile Phone Localization without War-Driving , 2010, 2010 Proceedings IEEE INFOCOM.

[16]  Qiang Wang,et al.  Energy efficient GPS sensing with cloud offloading , 2012, SenSys '12.

[17]  William G. Griswold,et al.  ActiveCampus: experiments in community-oriented ubiquitous computing , 2004, Computer.

[18]  Piotr Indyk,et al.  Faster GPS via the sparse fourier transform , 2012, Mobicom '12.

[19]  Moustafa Youssef,et al.  No need to war-drive: unsupervised indoor localization , 2012, MobiSys '12.

[20]  Yunhao Liu,et al.  Footprints elicit the truth: Improving global positioning accuracy via local mobility , 2013, 2013 Proceedings IEEE INFOCOM.

[21]  이영재,et al.  Differential GPS와 응용 , 1994 .

[22]  Dong-Hwan Hwang,et al.  A Step, Stride and Heading Determination for the Pedestrian Navigation System , 2004 .

[23]  J LaMance,et al.  ASSISTED GPS : A LOW-INFRASTRUCTURE APPROACH , 2002 .

[24]  Per Enge,et al.  The Wide Area Augmentation System , 1994 .