Abstract

Due to the influence of various sudden and abnormal factors during the tracking environment, equipment working conditions, and operation process, there are inevitable outliers in the tracking measurement process of aircraft such as carrier rockets, artificial satellites, and missiles. Therefore, the prerequisite for ensuring the reliability of processing results is to timely and accurately detect and correct outliers. In this paper, we proposed the sliding window-based variable degree B-spline function method (SWVD B-spline), which can handle isolated outliers and spotted outliers. SWVD B-spline uses variable degree B-spline function to model observed data in sliding windows, which can detect and correct outliers point by point along with window sliding. Then, we propose an initial window data selection method to remove outliers in initial windows to ensure the processing effect. In addition, because there are often inflection points in external ballistic velocity measurement data, differential evolution is used to optimize variable degree B-spline in windows that include inflection points to improve processing accuracy. The experimental results verify that SWVD B-spline can handle various outliers rapidly and efficiently.

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