Objective:A threshold filtering based adaptive unscented Kalman filtering method was proposed to address the issue of filter noise and interference signal effects caused by external disturbances in the system model of drones during spraying operations.Methods:By setting a threshold to determine whether it belonged to outliers,the weight of outliers was reduced,and the system model error caused by noise interference was reduced.The information fusion method of combination was applied to simplify the noise estimation process.Results:The MATLAB simulation results showed that compared with UKF,AUKF,simplified AUKF and the algorithm in this paper,the adaptive unscented Kalman algorithm based on threshold processing had improved the prediction accuracy of eastbound and northbound speeds by 57.9％and 54.1％respectively.Conclusion:The method had greatly improved the position accuracy,making the system more robust.
维普
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