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The Method of ADS-B Data Restraining Outliers on Self-adaptive Kalman Filter

Jian Dong

Abstract

In the actual filter processing of ADS-B data,the outliers in observation is the significant factors in influencing the fliter performance.By analysing the impact of outliers on fliter and data processing precision,through using the current statistical model of the Kalman filter algorithm for data processing and improving the gain matrices in self-adaptive Kalman filter,which is based on innovation,and presenting a method distinguishing and dealing with outliers.The simulation calculation shows that this method is of reliable performance and easy to operate,it can effectively eliminate the nagative impact of outliers on fliter and improve the accuary

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Key concepts: Outlier, Kalman filter, Computer science, Filter (signal processing), Data processing, Adaptive filter, Fast Kalman filter, Kernel adaptive filter