Application of Kalman Filtering in Preprocessing of Marine Buoy Data
[Objective]In order to improve the quality of ocean buoy data,automated data preprocessing methods were optimized.[Method]Based on the characteristics of ocean buoy data,an improved adaptive Kalman filter automated data preprocessing method was proposed.This method detected outliers through box plots,and used constrained variance to solve the problem of the filtering divergence caused by measurement noise.[Result and Conclusion]The results of offshore engineering applications and simulation experiments show that the improved algorithm has low computational cost and does not affect the normal collection and data fusion of the buoy system.The buoy data collection rate reaches 100%,and the cloud data center data reception rate reaches 97%;After outlier correction and filtering noise reduction,the raw data collected by the buoy becomes smoother and conforms to the law of time series variation.The data preprocessing effect is good.
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