Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/3690
Title: Improved Dead Reckoning Localization using IMU Sensor
Authors: Toy, I.
Durdu, A.
Yusefi, A.
Keywords: Autonomous vehicle
Dead Reckoning
IMU
Localization
Positioning Systems
Global positioning system
Navigation
Autonomous vehicle technologies
Autonomous Vehicles
Dead reckoning
Global Navigation Satellite Systems
Inertial measurements units
Localisation
Position estimation
Positioning system
Vehicle localization
Vehicle position
Autonomous vehicles
Publisher: Institute of Electrical and Electronics Engineers Inc.
Abstract: In the upcoming years, autonomous vehicle technology will advance quickly and spread widely. The most crucial component of such systems is vehicle localization or position estimation. The global navigation satellite system (GNSS) is the one of the most advanced positioning system currently in use. But the GNSS signals could be interrupted or degraded due to interference. Additionally, while GNSS delivers precise information for outdoor systems but is unable to provide a solution for indoor. An indoors-and-outdoors-usable device called an inertial measurement unit (IMU) sensor is employed in this paper to suggest a location estimate technique. The study's proposed IMU dead reckoning method makes use of novel techniques to filter noise data and accurately determine the position of the vehicle. The GNSS-based vehicle localization system can be improved by using this technique in GNSS-denied scenarios. In this paper, the IMU sensor's accelerometer, magnetometer, and gyroscope data are utilized to calculate the vehicle's velocity, orientation, and position. The experimental results on a real autonomous vehicle demonstrate that the system is effective, with average errors in rotation and translation of 1.03 degrees and 1.04 meters, respectively. © 2022 IEEE.
Description: Continental;et al.;Everseen;Huf;Nokia;Orange TM
15th International Symposium on Electronics and Telecommunications, ISETC 2022 -- 10 November 2022 through 11 November 2022 -- 186072
URI: https://doi.org/10.1109/ISETC56213.2022.10010239
https://hdl.handle.net/20.500.13091/3690
ISBN: 9781665451505
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections

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