Satellite telemetry data outlier elimination pre-processing method

Abstract

The invention provides a satellite telemetry data outlier elimination pre-processing method, comprising: firstly, analyzing the structures of the telemetry frame of the satellite, determining the frame length, identifying fields such as frame synchronization heads, frame counts, check bits and check modes in the telemetry frame; secondly, creating a reading pointer, successively searching the frame synchronization heads backwards, reading frame data to cache according to the frame length, taking out the frame count and the check bits, finally, calculating check bits according to the check modes of the satellite telemetry frame, comparing, judging whether the frame count is legal according to a satellite telemetry download rule, comparing with a former frame, if the frame counts of the former and the next frames are continuous and the check bits are right, illustrating that the frame data are right data; if the frame counts of the frame data and the former frame data are discontinuous and the check bits are wrong, illustrating that the frame data are outliers and are eliminated. According to the invention, double conditions of the check bits and frame counts are compared, the outliers are judged accurately, the method is easily realized through programming, and the elimination efficiency is high.

Description

technical field [0001] The present invention relates to the processing of satellite telemetry data, in particular to a preprocessing method for outlier elimination of satellite telemetry data. The outliers in are initially eliminated. Background technique [0002] The collection process of telemetry data is interfered by sensors, transducers, and radio transmission processes, and the received data often produces abnormal jump points, that is, incorrect points caused by measurement equipment and transmission. The data points that deviate from the changing law of the measured signal are called outliers. Data outliers seriously affect the processing and analysis of telemetry signals. The outlier points of slowly-varying signals will provide wrong information, while the outliers of rapidly-varying signals will generate false harmonic frequency components, which will increase the total level of noise. The outliers of will even overwhelm the invalid signal, giving a large error ...

AI Technical Summary

Problems solved by technology

Data outliers seriously affect the processing and analysis of telemetry signals. The outlier points of slowly-varying signals will provide wrong information, while the outliers of rapidly-varying signals will generate false harmonic frequency components, which will increase the total level of noise. The outlier value of will even overwhelm the invalid signal, giving a large error estimate of the total energy of the measured data

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