Effect of Vibration Suppression Device for GNSS/INS Integrated Navigation System Mounted on Self-Driving Vehicle
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
This paper presents a method to reduce the vibration-induced noise effect of an inertial measurement device mounted on a self-driving vehicle. The inertial sensor used in the GNSS/INS integrated navigation system of a self-driving vehicle is fixed directly on the chassis of vehicle body so that its navigation output is affected by the vibration of the vehicle's engine, resulting in the degradation of the navigational performance. Therefore, these effects must be considered when mounting the inertial sensor. In order to solve this problem, this paper proposes to use an in-house manufactured vibration suppression device and analyzes its impact on reducing the vibration effect. Experimental test results in a static scenario show that the vibrationinduced noise effect is more clearly observed in the lateral direction of the vehicle, but can be effectively suppressed by using the proposed vibration suppression device compared to the case without it. In addition, the dynamic positioning test scenario shows the position, speed, and posture errors are reduced to 74%, 67%, and 14% levels, respectively.
Abstract
This paper presents a method to reduce the vibration-induced noise effect of an inertial measurement device mounted on a self-driving vehicle. The inertial sensor used in the GNSS/INS integrated navigation system of a self-driving vehicle is fixed directly on the chassis of vehicle body so that its navigation output is affected by the vibration of the vehicle's engine, resulting in the degradation of the navigational performance. Therefore, these effects must be considered when mounting the inertial sensor. In order to solve this problem, this paper proposes to use an in-house manufactured vibration suppression device and analyzes its impact on reducing the vibration effect. Experimental test results in a static scenario show that the vibrationinduced noise effect is more clearly observed in the lateral direction of the vehicle, but can be effectively suppressed by using the proposed vibration suppression device compared to the case without it. In addition, the dynamic positioning test scenario shows the position, speed, and posture errors are reduced to 74%, 67%, and 14% levels, respectively.
참고문헌 (20)
- Bevly, D. M., "GNSS for Vehicle Control" (2009), Artech House
- Brown, R. G., "Introduction to random signals and applied Kalman filtering: with MATLAB exercises and solutions" (1997), John Wiley & Sons, Inc
- Cheng, G., "The Application of the Vibration Absorber in Laser Inertial Navigation Products", Journal of Sensors, 2021 (2021)[DOI]
- Dönmez, A., "Nonlinear vibration isolation of inertial measurement unit", Master, pp.2018
- Falco, G., "Loose and tight GNSS", INS integrations: Comparison of performance assessed in real urban scenarios, 2017, pp.17, 255~
- Gao, X., "RLAKF: An adaptive Kalman filter navigation algorithm based on reinforcement learning for ground vehicles", Remote Sensing, 12, pp.1704~ (2020)[DOI]
- Han, K., "Precise Positioning with Machine Learning based Kalman Filter using GNSS", IMU Measurements from Android Smartphone, 2021, 3094~3102
- Hao, Y., "A modified extended Kalman filter for a two-antenna GPS", INS vehicular navigation system, 2018, pp.18, 3809~
- 전경진, "승용차량의 아이들 진동을 고려한 착석자세에 따른 인체의 반응특성 분석", 한국소음진동공학회논문집, 20(12), pp.1121~1127 (2010), 한국소음진동공학회
- Kedadouche, M., "Design of a vibration isolator for the inertial navigation system of an autopilot dedicated to the operation of light drones", 2018 9th International Conference on Mechanical and Aerospace Engineering (ICMAE), pp.73~78 (2018)
- Mendel, J. M., "Lessons in Estimation Theory for Signal Processing, Communications, and Control" (1995), Prentice-Hall International
- Misra, P., "Global positioning system: Signals, Measurements, and Performance" (2006), Ganga-Jamuna Press
- Schütz, A., "Precise positioning through a loosely-coupled sensor fusion of GNSS-RTK, INS and LiDAR for autonomous driving", 2020 IEEE, 2020, 219~225
- Siouris, G., "Aerospace avionics systems: a modern synthesis" (1993), Academic Press
- Titterton, D. H., "Strapdown inertial navigation technology" (2004), Institution of Electrical Engineers
- Van Brummelen, J., "Autonomous vehicle perception: The technology of today and tomorrow", Transportation research part C: emerging technologies, 89, pp.384~406 (2018)[DOI]
- Wang, D., "Constrained MEMS-based GNSS", INS tightly coupled system with robust Kalman filter for accurate land vehicular navigation, 2020, pp.69, 5138~5148
- Wang, J., "Evaluation on loosely and tightly coupled GNSS", INS vehicle navigation system, 2017 (2017), 892~895
- Wang, J. J., "Improving adaptive Kalman Filter in GPS", SDINS integration with neural network, 2007, 571~578
- Yang, Y., "IMU signal software simulator", Proceedings of the 2007 National Technical Meeting of The Institute of Navigation, pp.532~538 (2007)
