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Aiming at the problem of positioning errors caused by terrain tilt, uneven soil hardness, and continuous turning during tractor operation in the field, a multisensor data fusion navigation positioning system based on GA-BP neural network training was designed. The integrated navigation system was mainly composed of RTK-GPS and IMU, and integrated GA-BP Kalman algorithm and error analysis. Based on multisensor navigation parameters, the positioning error of the tractor was corrected to make the tractors trajectory more stable. According to the established navigation and positioning system test platform based on the MK904 tractor, the original navigation and positioning information was obtained at the Luoyang Mengjin Yituo Product Test Base, and the algorithm was verified in Matlab. The test results showed that the accuracy of the roll angle of integrated navigation and positioning system was improved by 0.01rad when the tractor was driving straight; during continuous turning, the accuracy of the roll angle was increased by 0.02rad during the left turn, and the accuracy of the roll angle was increased by 0.04rad during the right turn. According to the error analysis and the digital characteristics of the positioning information, it can be obtained that the GA-BP Kalman algorithm can correct the GPS positioning error caused by field fluctuations, uneven soil hardness, and continuous turning to a certain extent, so that the tractors driving trajectory was more stable. It provided a reference for the followup research of tractor path tracking control. 