A Dead-Reckoning Based Local Positioning System for Intelligent Vehicles
- Resource Type
- Conference
- Authors
- Zhang, Meng; Yang, Jian; Zhao, Jifu; Dai, Yanjie
- Source
- 2019 IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS) Power, Intelligent Computing and Systems (ICPICS), 2019 IEEE International Conference on. :513-517 Jul, 2019
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Acceleration
Dead reckoning
Intelligent vehicles
Real-time systems
Kalman filters
Estimation
Filtering algorithms
dead reckoning
intelligent vehicle
local positioning
Kalman filter
- Language
This paper presents a local positioning system based on vehicle motion model. The system is designed by 2D dead reckoning principle, which uses previous state information, speed and heading outputs of vehicle sensors to estimate real-time pose information. A Kalman filter based on speed-acceleration model is introduced to eliminate error of the odometer. And a linear error model is introduced to compensate the accumulative error of gyroscope. By preprocessing the speed and heading outputs, the precision of local positioning system is improved.