Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-19T03:58:53.878Z Has data issue: false hasContentIssue false

Low Cost, High Accuracy Positioning In Urban Environments

Published online by Cambridge University Press:  23 August 2006

Chris Hide
Affiliation:
IESSG, University of Nottingham Email: [email protected]
Terry Moore
Affiliation:
IESSG, University of Nottingham Email: [email protected]
Chris Hill
Affiliation:
IESSG, University of Nottingham Email: [email protected]
David Park
Affiliation:
IESSG, University of Nottingham Email: [email protected]

Abstract

It is well known that GPS measurements are regularly obstructed in urban environments. Positioning accuracy in such environments is significantly degraded and in many areas, it is not possible to obtain a GPS position fix at all. There are currently two methods that can be used to improve availability in the urban environment. Firstly, GPS receivers can be augmented with dead reckoning sensors such as an INS. Alternatively, High Sensitivity GPS (HSGPS) receivers can be used which are able to acquire and track very weak signals. This paper assesses the performance obtained from a GPS and low cost INS integrated system and a HSGPS receiver in an urban environment in Nottingham, UK. The navigation systems are compared to a high accuracy integrated GPS/INS system which is used to provide a reference trajectory. It is demonstrated that the differential GPS and low cost INS system can provide horizontal positioning accuracy of better than 2·5 m RMS in real-time, and better than 1 m RMS in post-processing, whereas the non-differential HSGPS receiver provides a real-time performance of 5 m RMS. These results were obtained in an environment where, with conventional GPS receivers, a position solution is only available 48·4% of the time. Operational considerations such as initial alignment of the GPS and low cost INS are also discussed when comparing the two systems for urban positioning applications.

Type
Research Article
Copyright
Copyright © The Royal Institute of Navigation 2006

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Brown, R. B., Hwang, P. Y. C., 1997. Introduction to Random Signals and Applied Kalman Filtering, 3rd Edition. John Wiley and Sons Inc.Google Scholar
Gelb, A. (Ed.), 1974. Applied Optimal Estimation. Analytic Sciences Corporation.Google Scholar
Hide, C., 2003, Integration of GPS and low cost INS measurements, PhD thesis, University of Nottingham, September 2003.Google Scholar
Hide, C., Moore, T., 2005, GPS and Low Cost INS Integration for Positioning in the Urban Environment, In Proceedings of the Institute of Navigation GNSS 2005, Long Beach, CA, September 2005. To be published.Google Scholar
Lachapelle, G., Kuusniemi, H., Dao, D., MacGougan, G., Cannon, M. E., 2003, HSGPS Signal Analysis and Performance Under Various Indoor Conditions. Proceedings of the Institute of Navigation GPS 2003 Portland, Oregan, 9–12 September.Google Scholar
QinetiQ, 2004, The QinetiQ Q20 High Sensitivity GPS Receiver Module Datasheet, Document QINETIQ/FST/I&C/DS044398/1.0, version 1.0.Google Scholar
QinetiQ, 2004, High Sensitivity GPS Receiver Demonstration Kit User Guide, Document QINETIQ/FST/I&C/UG044388/1.0, August 2004.Google Scholar
Shin, E.-H. and El-Sheimy, N., 2002, Optimizing smoothing computation for near real-time GPS measurement gap filling in INS/GPS systems, In Proceedings of the Institute of Navigation GPS 2002.Google Scholar
van Diggelen, F., Abraham, C., 2001, Indoor GPS technology, Presented at CTIA Wireless-Agenda, Dallas, May 2001.Google Scholar
Watson, J. R. A, 2005, High-Sensitivity GPS L1 Signal Analysis for Indoor Channel Modelling, MSc thesis, University of Calgary, April 2005.Google Scholar