Database correlation method for multi-system location

Master's thesis

Research output: ThesisMaster's thesisTheses

Abstract

The future of the mobile positioning looks bright regardless of the fact that the growth in the markets of this field hasn’t been as good as it was anticipated to be a couple of years ago. A large variety of applications from friend finder services to vehicle navigation systems set different kinds of performance requirements for the applied positioning technique. Positioning accuracy is one of the most important performance measures. The accuracy of the satellite positioning techniques is generally better compared to the accuracy achieved with cellular network based positioning methods. In the near future, the
difference might even increase due to the introduction of the Assisted GPS (A-GPS) and Galileo satellite navigation system. In spite of this, the development and utilization of the cellular network based positioning methods can be justified. That is, because the satellite positioning requires special mobile terminals and it might take still several years before these terminals become popular. On the other hand, satellite positioning cannot be utilized everywhere.
The purpose of this work is to examine and enhance the Database Correlation Method (DCM) developed earlier at VTT. The enhancements consist of penalty term improvement, multi-system location and post-processing techniques including Kalman filter and Map-Matching algorithm. The theory including an overview of mobile positioning, the previous work related to database correlation and the introduction to the post-processing techniques is presented. Field measurements are carried out to collect terminal measurement data from real operating GSM and UMTS networks, and from WLAN indoor measurement campaign. These measurements are used to evaluate the implemented algorithms. The results of the performed positioning trials show that the enhancements do improve the positioning accuracy of the DCM algorithm. In conclusion, the DCM provides positioning accuracy suitable for many applications.
Original languageEnglish
QualificationMaster Degree
Awarding Institution
  • Helsinki University of Technology
Place of PublicationEspoo
Publisher
Publication statusPublished - 2005
MoE publication typeG2 Master's thesis, polytechnic Master's thesis

Fingerprint

Correlation methods
Satellites
Navigation systems
3G mobile communication systems
Global system for mobile communications
Processing
Wireless local area networks (WLAN)
Kalman filters
Global positioning system

Keywords

  • mobile positioning
  • database correlation
  • indoor positioning
  • Kalman filter
  • Map-Matching

Cite this

Kemppi, Paul. / Database correlation method for multi-system location : Master's thesis. Espoo : Helsinki University of Technology, 2005. 86 p.
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title = "Database correlation method for multi-system location: Master's thesis",
abstract = "The future of the mobile positioning looks bright regardless of the fact that the growth in the markets of this field hasn’t been as good as it was anticipated to be a couple of years ago. A large variety of applications from friend finder services to vehicle navigation systems set different kinds of performance requirements for the applied positioning technique. Positioning accuracy is one of the most important performance measures. The accuracy of the satellite positioning techniques is generally better compared to the accuracy achieved with cellular network based positioning methods. In the near future, thedifference might even increase due to the introduction of the Assisted GPS (A-GPS) and Galileo satellite navigation system. In spite of this, the development and utilization of the cellular network based positioning methods can be justified. That is, because the satellite positioning requires special mobile terminals and it might take still several years before these terminals become popular. On the other hand, satellite positioning cannot be utilized everywhere.The purpose of this work is to examine and enhance the Database Correlation Method (DCM) developed earlier at VTT. The enhancements consist of penalty term improvement, multi-system location and post-processing techniques including Kalman filter and Map-Matching algorithm. The theory including an overview of mobile positioning, the previous work related to database correlation and the introduction to the post-processing techniques is presented. Field measurements are carried out to collect terminal measurement data from real operating GSM and UMTS networks, and from WLAN indoor measurement campaign. These measurements are used to evaluate the implemented algorithms. The results of the performed positioning trials show that the enhancements do improve the positioning accuracy of the DCM algorithm. In conclusion, the DCM provides positioning accuracy suitable for many applications.",
keywords = "mobile positioning, database correlation, indoor positioning, Kalman filter, Map-Matching",
author = "Paul Kemppi",
note = "CA: TTE Diplomity{\"o} Helsinki University of Technology, Department of Electrical and COmmunications Engineering",
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language = "English",
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Kemppi, P 2005, 'Database correlation method for multi-system location: Master's thesis', Master Degree, Helsinki University of Technology, Espoo.

Database correlation method for multi-system location : Master's thesis. / Kemppi, Paul.

Espoo : Helsinki University of Technology, 2005. 86 p.

Research output: ThesisMaster's thesisTheses

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T1 - Database correlation method for multi-system location

T2 - Master's thesis

AU - Kemppi, Paul

N1 - CA: TTE Diplomityö Helsinki University of Technology, Department of Electrical and COmmunications Engineering

PY - 2005

Y1 - 2005

N2 - The future of the mobile positioning looks bright regardless of the fact that the growth in the markets of this field hasn’t been as good as it was anticipated to be a couple of years ago. A large variety of applications from friend finder services to vehicle navigation systems set different kinds of performance requirements for the applied positioning technique. Positioning accuracy is one of the most important performance measures. The accuracy of the satellite positioning techniques is generally better compared to the accuracy achieved with cellular network based positioning methods. In the near future, thedifference might even increase due to the introduction of the Assisted GPS (A-GPS) and Galileo satellite navigation system. In spite of this, the development and utilization of the cellular network based positioning methods can be justified. That is, because the satellite positioning requires special mobile terminals and it might take still several years before these terminals become popular. On the other hand, satellite positioning cannot be utilized everywhere.The purpose of this work is to examine and enhance the Database Correlation Method (DCM) developed earlier at VTT. The enhancements consist of penalty term improvement, multi-system location and post-processing techniques including Kalman filter and Map-Matching algorithm. The theory including an overview of mobile positioning, the previous work related to database correlation and the introduction to the post-processing techniques is presented. Field measurements are carried out to collect terminal measurement data from real operating GSM and UMTS networks, and from WLAN indoor measurement campaign. These measurements are used to evaluate the implemented algorithms. The results of the performed positioning trials show that the enhancements do improve the positioning accuracy of the DCM algorithm. In conclusion, the DCM provides positioning accuracy suitable for many applications.

AB - The future of the mobile positioning looks bright regardless of the fact that the growth in the markets of this field hasn’t been as good as it was anticipated to be a couple of years ago. A large variety of applications from friend finder services to vehicle navigation systems set different kinds of performance requirements for the applied positioning technique. Positioning accuracy is one of the most important performance measures. The accuracy of the satellite positioning techniques is generally better compared to the accuracy achieved with cellular network based positioning methods. In the near future, thedifference might even increase due to the introduction of the Assisted GPS (A-GPS) and Galileo satellite navigation system. In spite of this, the development and utilization of the cellular network based positioning methods can be justified. That is, because the satellite positioning requires special mobile terminals and it might take still several years before these terminals become popular. On the other hand, satellite positioning cannot be utilized everywhere.The purpose of this work is to examine and enhance the Database Correlation Method (DCM) developed earlier at VTT. The enhancements consist of penalty term improvement, multi-system location and post-processing techniques including Kalman filter and Map-Matching algorithm. The theory including an overview of mobile positioning, the previous work related to database correlation and the introduction to the post-processing techniques is presented. Field measurements are carried out to collect terminal measurement data from real operating GSM and UMTS networks, and from WLAN indoor measurement campaign. These measurements are used to evaluate the implemented algorithms. The results of the performed positioning trials show that the enhancements do improve the positioning accuracy of the DCM algorithm. In conclusion, the DCM provides positioning accuracy suitable for many applications.

KW - mobile positioning

KW - database correlation

KW - indoor positioning

KW - Kalman filter

KW - Map-Matching

M3 - Master's thesis

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CY - Espoo

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Kemppi P. Database correlation method for multi-system location: Master's thesis. Espoo: Helsinki University of Technology, 2005. 86 p.