Improving the Reliability of GPS and GLONASS Navigation Solution in Urban Canyons using a Tuned Kalman Filter

Document Type : Original Article

Authors

1 Department of Electrical Engineering, Iran University of Science and Technology

2 Samara National Research University, 34, Moskovskoye shosse, Samara, 443086, Russia

Abstract

Abstract: Urban canyon is categorized as hard environment for positioning of a dynamic vehicle due to low number and also bad configuration of in-view satellites. In this paper, a tuning procedure is proposed to adjust the important factors in Kalman Filter (KF) using Genetic Algorithm (GA). The authors tested the algorithm on a dynamic vehicle in an urban canyon with hard condition and compared the results with traditional KF and Weighted Least Square (WLS) methods. The outputs showed that this algorithm could be more reliable more than 114% and 61% against WLS and traditional KF.
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Abstract: Urban canyon is categorized as hard environment for positioning of a dynamic vehicle due to low number and also bad configuration of in-view satellites. In this paper, a tuning procedure is proposed to adjust the important factors in Kalman Filter (KF) using Genetic Algorithm (GA). The authors tested the algorithm on a dynamic vehicle in an urban canyon with hard condition and compared the results with traditional KF and Weighted Least Square (WLS) methods. The outputs showed that this algorithm could be more reliable more than 114% and 61% against WLS and traditional KF.

Keywords

Main Subjects

Article Title [فارسی]

Improving the Reliability of GPS and GLONASS Navigation Solution in Urban Canyons using a Tuned Kalman Filter

Authors [فارسی]

  • A.علی خاوری 1
  • سید محمدرضا موسوی 1
  • امیر طباطبایی 2
  • هادی شهریار شاه حسینی 1
1 دانشگاه علم و صنعت ایران
Abstract [فارسی]

Abstract: Urban canyon is categorized as hard environment for positioning of a dynamic vehicle due to low number and also bad configuration of in-view satellites. In this paper, a tuning procedure is proposed to adjust the important factors in Kalman Filter (KF) using Genetic Algorithm (GA). The authors tested the algorithm on a dynamic vehicle in an urban canyon with hard condition and compared the results with traditional KF and Weighted Least Square (WLS) methods. The outputs showed that this algorithm could be more reliable more than 114% and 61% against WLS and traditional KF.
---------------------------------------------------------------------------------------
Abstract: Urban canyon is categorized as hard environment for positioning of a dynamic vehicle due to low number and also bad configuration of in-view satellites. In this paper, a tuning procedure is proposed to adjust the important factors in Kalman Filter (KF) using Genetic Algorithm (GA). The authors tested the algorithm on a dynamic vehicle in an urban canyon with hard condition and compared the results with traditional KF and Weighted Least Square (WLS) methods. The outputs showed that this algorithm could be more reliable more than 114% and 61% against WLS and traditional KF.

Keywords [فارسی]

  • GPS
  • GLONASS
  • Urban canyon positioning
  • Kalman Filter
  • Weighted least square

References

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Journal of Aerospace Science and Technology
Volume 12, Issue 2
Summer and Autumn 2019
Pages 11-18

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