Spacecraft outer trajectory tracking data spot type outlier identification and correction method

Abstract

The invention discloses a spacecraft external ballistic trajectory tracking data spot type outlier identification and correction method, which specifically comprises the steps of firstly, establishinga spacecraft external ballistic trajectory tracking data time sequence mathematical model containing a spot type outlier; segmenting the spacecraft outer trajectory tracking data; solving the standard deviation of the tracking data of the outer trajectory of each section of spacecraft; estimating parameters of the spacecraft outer trajectory tracking data model; identifying and correcting spot type outliers in the outer trajectory tracking data of each section of the spacecraft; and finally, splicing the spacecraft outer trajectory tracking data of each section after the outliers are identified and corrected. According to the method, the spot type outliers in the spacecraft outer trajectory tracking data can be automatically recognized, high-precision correction is carried out, and time consumption and personnel consumption for professional staff to judge and correct the spot type outliers in a human eye mode are avoided.

Description

technical field [0001] The invention belongs to the technical field of aerospace tracking data processing, and in particular relates to a spot-type outlier identification and correction method for ballistic tracking data outside a spacecraft. Background technique [0002] Due to the impact of various sudden changes in the tracking environment, equipment working conditions, and operating processes, in the tracking and measurement data of various aircraft such as launch vehicles, artificial satellites, and missiles, there are inevitably some abnormal data, abnormal points, etc. (Outliers) and other small parts of data that obviously deviate from the trend of most normal data points (Inliers), these abnormal data are called outliers. Decades of space launch measurement and control practice and a large number of theoretical research, simulation analysis, and application practice at home and abroad show that outliers have a great destructive effect on the classical processing met...

AI Technical Summary

Problems solved by technology

The traditional outlier elimination methods (including Wright criterion, Romanowski criterion, Grubbs criterion and Chauvier criterion, etc.) have constraints on the statistical difference characteristics of ballistic data, which makes these methods limited in use; The value filtering and difference method can effectively eliminate spot-type outliers, but the elimination effect is unstable, and data distortion or missing will occur; the extrapolation fitting method can effectively eliminate isolated and spot-type outliers, but the spot-type outliers will be eliminated after removal. missing data

At present, there is no effective method to identify and correct the spot-type outliers in the external ballistic tracking measurement data

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