JOURNAL ARTICLE

Precise outdoor localization with a GPS–INS integration system

Wonkyo SeoSeoyoung HwangJaehyun ParkJang-Myung Lee

Year: 2012 Journal:   Robotica Vol: 31 (3)Pages: 371-379   Publisher: Cambridge University Press

Abstract

SUMMARY This paper proposes a precise outdoor localization algorithm with the integration of Global Positioning System (GPS) and Inertial Navigation System (INS). To achieve precise outdoor localization, two schemes are recently proposed, which consist of de-noising the INS signals and fusing the GPS and INS data. To reduce the noise from the internal INS sensors, the discrete wavelet transform and variable threshold method are utilized, and to fuse the GPS and INS data while filtering out the noise caused by the acceleration, deceleration, and unexpected slips, the Unscented Particle Filter (UPF) is adopted. Conventional de-noising methods mainly employ a combination of low-pass and high-pass filters, which results in signal distortion. This newly proposed system also utilizes the vibration information of the actuator according to the fluctuations of the velocity to minimize the signal distortion. The UPF resolves the nonlinearities of the actuator and non-normal distributions of the noise more effectively than the conventional particle filter (PF) or Extended Kalman Filter–PF. The superiority of the proposed algorithm was verified through experiments, and the results are reported.

Keywords:
Global Positioning System GPS/INS Computer science Noise (video) Kalman filter GPS signals Distortion (music) Inertial navigation system Acceleration Particle filter SIGNAL (programming language) Control theory (sociology) Inertial measurement unit Filter (signal processing) Assisted GPS Artificial intelligence Computer vision Inertial frame of reference Telecommunications Physics

Metrics

12
Cited By
0.66
FWCI (Field Weighted Citation Impact)
29
Refs
0.73
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Indoor and Outdoor Localization Technologies
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence
Inertial Sensor and Navigation
Physical Sciences →  Engineering →  Aerospace Engineering

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