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Shadow Matching: A New GNSS Positioning Technique for Urban Canyons

  • Paul D. Groves (a1)
Abstract

The Global Positioning System (GPS) is unreliable in dense urban areas, known as urban canyons, which have tall buildings or narrow streets. This is because the buildings block the signals from many of the satellites. Combining GPS with other Global Navigation Satellite Systems (GNSS) significantly increases the availability of direct line-of-sight signals. Modelling is used to demonstrate that, although this will enable accurate positioning along the direction of the street, the positioning accuracy in the cross-street direction will be poor because the unobstructed satellite signals travel along the street, rather than across it. A novel solution to this problem is to use 3D building models to improve cross-track positioning accuracy in urban canyons by predicting which satellites are visible from different locations and comparing this with the measured satellite visibility to determine position. Modelling is used to show that this shadow matching technique has the potential to achieve metre-order cross-street positioning in urban canyons. The issues to be addressed in developing a robust and practical shadow matching positioning system are then discussed and solutions proposed.

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Corresponding author
(Email: p.groves@ucl.ac.uk)
References
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[1]Ballester-Gúrpide, Í., et al. (2000) “Future GNSS Constellation Performances inside Urban Environments,” Proc. ION GPS 2000, Salt Lake City, UT, September, 24362445.
[2]Lachapelle, G., et al. (1997) “Augmentation of GPS/GLONASS For Vehicular Navigation Under Signal Masking,” Proc. ION GPS 1997, Kansas City, MO, September 15111519.
[3]Tsakiri, M, et al. , (1998) “Urban Fleet Monitoring with GPS and GLONASS,” The Journal of Navigation, 51, 382393.
[4]Ji, S., et al. (2009) “Potential Benefits of GPS/GLONASS/GALILEO Integration in an Urban canyon-Hong Kong,” Proc. Global Navigation Satellite System: Technology Innovation and Application, Beijing, China, August, 390399.
[5]Ercek, R., De Doncker, P. and Grenez, F., (2005) “Study of Pseudo-Range Error Due to Non-Line-of-Sight-Multipath in Urban Canyons,” Proc. ION GNSS 2005, Long Beach, CA, September 10831094.
[6]Viandier, N., et al. (2008) “GNSS Performance Enhancement in Urban Environment Based on Pseudo-range Error Model,” Proc. IEEE/ION PLANS 2008, Monterey, CA, May, 377382.
[7]Bradbury, J. et al. (2007) “Code Multipath Modelling in the Urban Environment Using Large Virtual Reality City Models: Determining the Local Environment,” The Journal of Navigation, 60, 95–105.
[8]Chen, R., et al. (2009) “Development of a 3D Personal Navigation and LBS System with Demonstration in Shanghai EXPO in 2010,” Proc. ION GNSS 2009, Savannah, GA, September, 21242129.
[9]Groves, P. D. (2008) Principles of GNSS, Inertial and Multi-Sensor Integrated Navigation Systems, Artech House.
[10]Conley, R. et al. (2006) “Performance of Stand-Alone GPS,” In Understanding GPS Principles and Applications, Second Edition, Kaplan, E. D. and Hegarty, C. J., (eds), Norwood, MA: Artech House, 301378.
[11]Swinford, R. P. (2005) “Building on-the-fly world models for pervasive gaming and other ubicomp applications using GPS availability data,” Proc. IEE International Workshop on Intelligent Environments, Colchester, UK, 133142.
[12]Brown, R. G. (1996) “Receiver Autonomous Integrity Monitoring,” In Global Positioning System: Theory and Applications Volume II, Parkinson, B. W. and Spilker, J. J. Jr. (Eds), AIAA, 143165.
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The Journal of Navigation
  • ISSN: 0373-4633
  • EISSN: 1469-7785
  • URL: /core/journals/journal-of-navigation
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