%0 Conference Proceedings
%T A Low-Cost Positioning System for Parallel Tracking Applications of Agricultural Vehicles by Using Kalman Filter
%+ Ningbo Institute of Technology (NIT)
%+ Ningbo Yinzhou Micro Agriculture Technology Ltd.
%+ Zhejiang University
%A Zhang, Fangming
%A Feng, Ximing
%A Li, Yuan
%A Rao, Xiuqin
%A Cui, Di
%Z Part 1: Decision Support Systems, Intelligent Systems and Artificial Intelligence Applications
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 5th Computer and Computing Technologies in Agriculture (CCTA)
%C Beijing, China
%Y Daoliang Li
%Y Yingyi Chen
%I Springer
%3 Computer and Computing Technologies in Agriculture V
%V AICT-368
%N Part I
%P 461-470
%8 2011-10-29
%D 2011
%R 10.1007/978-3-642-27281-3_52
%K Positioning system
%K GPS
%K Kalman filter
%K parallel tracking
%K low-cost
%Z Computer Science [cs]Conference papers
%X A position-velocity (PV) model and a multi-sensor system, consisted of a consumer application GPS, a MEMS gyro, two encoders, and a turning angle sensor, was constructed for the positioning system. The two encoders augmented the positioning accuracy greatly that the fluctuation of vehicle position was greatly smoothed comparing with a GPS-only system. The minimal fluctuation was falling from 2.21 m to 0.52 m (east direction), from 0.68 m to 0.23 m (north direction). The maximum XTE was reduced from 2.5 m to 0.77 m, and the RMS value was improved to 0.22m. The GPS bias error was the major difficulty to produce better performance.
%G English
%Z TC 5
%Z WG 5.14
%2 https://inria.hal.science/hal-01351848/document
%2 https://inria.hal.science/hal-01351848/file/978-3-642-27281-3_52_Chapter.pdf
%L hal-01351848
%U https://inria.hal.science/hal-01351848
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC5
%~ IFIP-WG5-14
%~ IFIP-CCTA
%~ IFIP-AICT-368