A satellite telemetry data outlier detection method, device and electronic equipment

By training a nuclear extreme learning machine to establish an outlier detection model for satellite telemetry data, the problem of low efficiency and accuracy in outlier detection in telemetry data was solved, and efficient and accurate outlier identification was achieved.

CN115563092BActive Publication Date: 2026-07-03TSINGHUA UNIVERSITY
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Patent Information

Application Number
CN202211172987.6
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2022-09-26
Publication Date
2026-07-03
Estimated Expiration
2042-09-26

AI Technical Summary

Technical Problem

Existing technologies struggle to efficiently and accurately detect outliers in satellite telemetry data in harsh space environments, especially telemetry data anomalies caused by single-event latch-up due to high-energy particles and other factors.

Method used

A nuclear extreme learning machine was used to train satellite telemetry data to establish an outlier detection model. The telemetry data was then processed using the trained model, and the optimized correlation coefficient was used to determine whether the telemetry data was an outlier.

Benefits of technology

It improves the efficiency and accuracy of outlier detection in telemetry data, effectively identifies outliers in telemetry data, and reduces the false alarm rate.

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Abstract

This application provides a method, apparatus, and electronic device for detecting outliers in satellite telemetry data. The outlier detection model for telemetry data is trained using a kernel extreme learning machine, which can effectively detect outliers in satellite telemetry data, greatly improving the efficiency and accuracy of outlier detection.
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