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Article

Numerical Analysis of GNSS Signal Outage Effect on EOPs Solutions Using Tightly Coupled GNSS/IMU Integration: A Simulated Case Study in Sweden

by
Arash Jouybari
1,*,
Mohammad Bagherbandi
1,2 and
Faramarz Nilfouroushan
1,3
1
Faculty of Engineering and Sustainable Development, University of Gävle, SE-80176 Gävle, Sweden
2
Division of Surveying-Geodesy, Land Law and Real Estate Planning, Royal Institute of Technology (KTH), SE-10044 Stockholm, Sweden
3
Department of Geodetic Infrastructure, Geodata Division, Lantmäteriet, SE-80182 Gävle, Sweden
*
Author to whom correspondence should be addressed.
Sensors 2023, 23(14), 6361; https://doi.org/10.3390/s23146361
Submission received: 24 April 2023 / Revised: 30 June 2023 / Accepted: 4 July 2023 / Published: 13 July 2023
(This article belongs to the Section Electronic Sensors)

Abstract

The absence of a reliable Global Navigation Satellite System (GNSS) signal leads to degraded position robustness in standalone receivers. To address this issue, integrating GNSS with inertial measurement units (IMUs) can improve positioning accuracy. This article analyzes the performance of tightly coupled GNSS/IMU integration, specifically the forward Kalman filter and smoothing algorithm, using both single and network GNSS stations and the post-processed kinematic (PPK) method. Additionally, the impact of simulated GNSS signal outage on exterior orientation parameters (EOPs) solutions is investigated. Results demonstrate that the smoothing algorithm enhances positioning uncertainty (RMSE) for north, east, and heading by approximately 17–43% (e.g., it improves north RMSE from 51 mm to a range of 42 mm, representing a 17% improvement). Orientation uncertainty is reduced by about 60% for roll, pitch, and heading. Moreover, the algorithm mitigates the effects of GNSS signal outage, improving position uncertainty by up to 95% and orientation uncertainty by up to 60% using the smoothing algorithm instead of the forward Kalman filter for signal outages up to 180 s.
Keywords: GNSS/INS integration; forward Kalman filter; smoothing algorithm; tightly coupled; PPK; virtual reference station; aerial photogrammetry GNSS/INS integration; forward Kalman filter; smoothing algorithm; tightly coupled; PPK; virtual reference station; aerial photogrammetry

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MDPI and ACS Style

Jouybari, A.; Bagherbandi, M.; Nilfouroushan, F. Numerical Analysis of GNSS Signal Outage Effect on EOPs Solutions Using Tightly Coupled GNSS/IMU Integration: A Simulated Case Study in Sweden. Sensors 2023, 23, 6361. https://doi.org/10.3390/s23146361

AMA Style

Jouybari A, Bagherbandi M, Nilfouroushan F. Numerical Analysis of GNSS Signal Outage Effect on EOPs Solutions Using Tightly Coupled GNSS/IMU Integration: A Simulated Case Study in Sweden. Sensors. 2023; 23(14):6361. https://doi.org/10.3390/s23146361

Chicago/Turabian Style

Jouybari, Arash, Mohammad Bagherbandi, and Faramarz Nilfouroushan. 2023. "Numerical Analysis of GNSS Signal Outage Effect on EOPs Solutions Using Tightly Coupled GNSS/IMU Integration: A Simulated Case Study in Sweden" Sensors 23, no. 14: 6361. https://doi.org/10.3390/s23146361

APA Style

Jouybari, A., Bagherbandi, M., & Nilfouroushan, F. (2023). Numerical Analysis of GNSS Signal Outage Effect on EOPs Solutions Using Tightly Coupled GNSS/IMU Integration: A Simulated Case Study in Sweden. Sensors, 23(14), 6361. https://doi.org/10.3390/s23146361

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