Citation: Lee, Y. D., Lee, T. G., & Lee, H. K., 2023, Performance Evaluation of a Compressed-State Constraint Kalman Filter for a Visual/Inertial/GNSS Navigation System, Journal of Positioning, Navigation, and Timing, 12, 129-140.
Journal of Positioning, Navigation, and Timing (J Position Navig Timing) 2023 June, Volume 12, Issue 2, pages 129-140. https://doi.org/10.11003/JPNT.2023.12.2.129
Received on 11 April 2023, Revised on 01 May 2023, Accepted on 06 May 2023, Published on 30 June 2023.
License: Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/bync/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Yu Dam Lee, Taek Geun Lee, Hyung Keun Lee†
Department of Electronics and Information Engineering, Korea Aerospace University, Gyeonggi-do 10540, Korea
†Corresponding Author: E-mail, hyknlee@kau.ac.kr; Tel: +82-2-300-0131 Fax: +82-2-3158-5769
Autonomous driving systems are likely to be operated in various complex environments. However, the well-known integrated Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS), which is currently the major source for absolute position information, still has difficulties in accurate positioning in harsh signal environments such as urban canyons. To overcome these difficulties, integrated Visual/Inertial/GNSS (VIG) navigation systems have been extensively studied in various areas. Recently, a Compressed-State Constraint Kalman Filter (CSCKF)-based VIG navigation system (CSCKF-VIG) using a monocular camera, an Inertial Measurement Unit (IMU), and GNSS receivers has been studied with the aim of providing robust and accurate position information in urban areas. For this new filter-based navigation system, on the basis of timepropagation measurement fusion theory, unnecessary camera states are not required in the system state. This paper presents a performance evaluation of the CSCKF-VIG system compared to other conventional navigation systems. First, the CSCKF-VIG is introduced in detail compared to the well-known Multi-State Constraint Kalman Filter (MSCKF). The CSCKF-VIG system is then evaluated by a field experiment in different GNSS availability situations. The results show that accuracy is improved in the GNSS-degraded environment compared to that of the conventional systems.
visual-inertial odometry, multi-GNSS, multi-sensor fusion, compression filter
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Conceptualization, Y. D. Lee; methodology, Y. D. Lee; software, Y. D. Lee; validation, Y. D. Lee; formal analysis, Y. D. Lee, H. K. Lee; investigation, Y. D. Lee; resources, H. K. Lee; data curation, Y. D. Lee, T. G. Lee; writing, Y. D. Lee; review and editing, H. K. Lee; supervision, H. K. Lee.
The authors declare no conflict of interest.