Map matching with kalman filter and location estimation

Ziya Gökalp Ersan; Metin Zontul; İlkay Yelmen

doi:10.17776/csj.634940

EN

Map matching with kalman filter and location estimation

Abstract

Known as Global Navigation Satellite Systems, GNSS is a geolocation service. GNSS systems used in the world are known as GPS in America, GLONASS in Russia, GALILEO in Europe, BEIDOU in China and IRNSS in India. However, GPS is the only one that works decisively today. GNSS systems are used effectively in the navigation of all types of land, sea and air vehicles such as search and rescue, target finding, and landing and take-off of airplanes with or without limited visibility. However, when environmental and weather conditions are unfavorable, the accuracy of the GPS systems in the GNSS may vary. This study is presented as a solution to the map matching problem by minimizing the error deviation rates of GPS data from NOVATEL and UBLOX based vehicle tracking devices with the help of Kalman Filter Algorithm. In addition, the deviation rate between the GPS data from the vehicle tracking system and the estimated point coordinates is provided in meters.

Keywords

Map Matching,Kalman Filter,Location Estimation,GPS

References

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Details

Primary Language

English

Subjects

-

Journal Section

Research Article

Authors

Ziya Gökalp Ersan ^*
0000-0002-2575-0735
Türkiye

Metin Zontul
0000-0002-7557-2981
Türkiye

İlkay Yelmen
0000-0002-1684-9717
Türkiye

Publication Date

March 22, 2020

Submission Date

October 19, 2019

Acceptance Date

February 11, 2020

Published in Issue

Year 2020 Volume: 41 Number: 1

DOI

https://doi.org/10.17776/csj.634940

IZ

https://izlik.org/JA66MZ96MN

Cite

RIS / Bibtex

APA

Ersan, Z. G., Zontul, M., & Yelmen, İ. (2020). Map matching with kalman filter and location estimation. Cumhuriyet Science Journal, 41(1), 43-48. https://doi.org/10.17776/csj.634940

Cited By

Implementation of a Kalman Filter for Noise Reduction on the INA219 Current Sensor

American Journal of Electrical and Computer Engineering

https://doi.org/10.11648/j.ajece.20250902.14

Öz

Map matching with kalman filter and location estimation

Abstract

Keywords

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

Cite

Cited By

Implementation of a Kalman Filter for Noise Reduction on the INA219 Current Sensor