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IMM EKF based Sensor Fusion of GPS with In-Vehicle Sensors for Vehicle Positioning Under Various Road Surface Conditions

Title
IMM EKF based Sensor Fusion of GPS with In-Vehicle Sensors for Vehicle Positioning Under Various Road Surface Conditions
Author
정정주
Keywords
Autonomous Driving; Interacting Multiple Model; Kalman Filter algorithm; Vehicle Positioning
Issue Date
2020-10
Publisher
ICROS
Citation
2020 20th International Conference on Control, Automation and Systems (ICCAS), page. 1220-1224
Abstract
In this paper, we propose an estimation of the accurate vehicle position using Interacting Multiple Model Extended Kalman Filter (IMM EKF) when road surface varies. Since the vehicle has different cornering stiffness as the road surface varies, it is difficult to accurately estimate the position of the vehicle. To resolve this problem, we present the IMM EKF considering each model of different roads to improve the estimation performance. From the numerical simulation using MATLAB/CARSIM, we observed that the performance of the proposed algorithm improves vehicle positioning performance.
URI
https://ieeexplore.ieee.org/document/9268405https://repository.hanyang.ac.kr/handle/20.500.11754/171828
ISBN
978-89-93215-20-5; 978-1-7281-8562-0
ISSN
2642-3901; 1598-7833
DOI
10.23919/ICCAS50221.2020.9268405
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > ELECTRICAL AND BIOMEDICAL ENGINEERING(전기·생체공학부) > Articles
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