A Low-Cost Positioning System for Parallel Tracking Applications of Agricultural Vehicles by Using Kalman Filter

Abstract : 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.
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Daoliang Li; Yingyi Chen. 5th Computer and Computing Technologies in Agriculture (CCTA), Oct 2011, Beijing, China. Springer, IFIP Advances in Information and Communication Technology, AICT-368 (Part I), pp.461-470, 2012, Computer and Computing Technologies in Agriculture V. 〈10.1007/978-3-642-27281-3_52〉
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Fangming Zhang, Ximing Feng, Yuan Li, Xiuqin Rao, Di Cui. A Low-Cost Positioning System for Parallel Tracking Applications of Agricultural Vehicles by Using Kalman Filter. Daoliang Li; Yingyi Chen. 5th Computer and Computing Technologies in Agriculture (CCTA), Oct 2011, Beijing, China. Springer, IFIP Advances in Information and Communication Technology, AICT-368 (Part I), pp.461-470, 2012, Computer and Computing Technologies in Agriculture V. 〈10.1007/978-3-642-27281-3_52〉. 〈hal-01351848〉

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