Automatic Navigation Method for Agricultural Machinery Based on GNSS/MIMU/DR Information Fusion

Liu Jinyi, Du Yuefeng, Zhang Shuo, Zhu Zhongxiang, Mao Enrong, Chen Yu

Abstract

The real time accurate position update technology of agricultural machinery was one of the most important studies in agricultural machinery automatic navigation system, and it has a very important significance to improve the efficiency of intelligent agricultural production. However, in the field operation of agricultural machinery automatic navigation system, the situations that the number of satellite was unstable, the GPS signal was blocked, and data transmission was wrong would cause low location precision and poor stability. In order to solve the above problems, a two dimensional kinematic model of agricultural machinery was built, and an adaptive extended Kalman filtering algorithm which adjusted the system’s state covariance was carried out based on the integrated navigation system of GNSS/MIMU/DR. The algorithm was used to compute the difference of present estimate and predictive value. When the difference became greater, it showed that the system state had changed greatly, so as to make appropriate adjustments to the system state covariance matrix for better filtering. The algorithm was verified by static test and linear guide rail test to accurately evaluate the accuracy of the integrated navigation and positioning system. The tests indicated that: in static state, the average value deviation of heading was 0.0014°, the maximum deviation was 0.0998°, the standard deviation was 0.0474°, and the position average deviation was 0.0037m, the maximum deviation was 0.0081m, the standard deviation was 0.0010m; in straight rail state, the average value deviation of heading was 0.0245°, the maximum deviation was 0.4324°, the standard deviation was 0.2511°, and the position average deviation was 0.0076m, the maximum deviation was 0.0186m, the standard deviation was 0.0044m. All the different evaluations proved that the adjusted filtering was superior to the traditional filtering, which indicated the necessity and superiority of the proposed algorithm. At the same time, it is proved that the method can satisfy the accuracy and stability requirements of the agricultural machinery navigation and positioning system.


Keywords: agricultural machinery, navigation, information fusion, global navigation satellite system, miniature inertial measurement unit, extended Kalman filtering algorithm

 

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HUANG J Y, TSAI С H. Improve GPS positioning accuracy with context awareness[C] //IEEE International Conference on Ubi- Media Computing, 2008:154 - 159.

FENG Lei. Study on navigation system for off-road vehicle guidance based on GPS and sensor technolog}’[ D ]. Hangzhou: Zhejiang University, 2004. (in Chinese)

LIU Xiaoguang, HU Jingtao, BAI Xiaoping, et al. Research on multi-sensor integrated navigation for transplanted[ J ]. Agricultural Mechanization Research, 2014(5) :24 -30. (in Chinese)

REID J F, QIN Z, NOGUCHI N, et al. Agricultural automatic guidance research in north America[J]. Computers & Electronics in Agriculture, 2000, 25(1 -2) : 155 - 167.

ZHOU Jianjun, WANG Xiu, ZHANG Rui, et al. GPS/DR integrated navigation positioning method for agricultural machineryf J ]. Transactions of the Chinese Society for Agricultural Machinery, 2012, 43(Supp. ) :262 -265. (in Chinese)

ZHU Zhongxiang, HAN Keli, SONG Zhenghe, et al. Fusion positioning method based on weighted-confidence for tractor integrated navigation[ J ]. Transactions of the Chinese Society for Agricultural Machinery, 2013 ,44( Supp. 1 ) : 210 -215. (in Chinese)

LI Ang, WANG Wei, WU Jianan. Design in low-cost integrated navigation system[J]. Measurement & Control Technology, 2012, 31(8); 12 — 15. (in Chinese)

XU Yong, HE Xiufeng. Design of GPS/IMU integration for positioning and orientation[ J]. GNSS World of China, 2(X)4, 29(4) ; 24 -28. (in Chinese)

JIA Ruicai, WU Cailun, ZHI Qinan, et al. Research on lower cost MEMS IMU and GPS integrating algorithm [С ] //China Satellite Navigation Conference, 2013. (in Chinese)

YANG Rongrong, ZHANG Ling. Application of UKF in vehicle integrated positioning technology [ J ]. Science Technology and Engineering, 2010, 10(25 ) ; 6310 -6313. (in Chinese)

KOU Yanhong, ZHANG Qishan, LI Xianliang. Data fusion algorithm for GPS/DR integrated vehicle navigation system [ J ]. Journal of Beijing University of Aeronautics and Astronautics, 2003, 29(3) :264 -268. (in Chinese)

LIU Xu, ZHANG Qishan, YANG Dongkai. Nonlinear filter algorithm for GPS/DR integrated positioning[ J]. Journal of Beijing University of Aeronautics and Astronautics, 2007, 33(2) : 184 - 187. (in Chinese)

WEI Wei, QIN Yongyuan, ZHANG Xiaodong, et al. Amelioration of the Sage _ Husa algorithm[ J ]. Journal of Chinese Inertial Technology, 2012,20(6) :678 -686. (in Chinese)

ZHANG Jing, CHEN Du, WANG Shumao, et al. Research of INS/GNSS heading information fusion method for agricultural machinery automatic navigation system[J]. Transactions of the Chinese Society for Agricultural Machinery, 2015 ,46( Supp. ) ; 1-7. (in Chinese)

LI Shixin, WANG Yanfei, YANG Ye, et al. Velocity matching alignment of low cost INS/GPS integrated system[J]. Journal of Chinese Inertial Technology, 2005, 13( 1 ) :35 -37. (in Chinese)


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