Detection element consistency detection method for large-array multi-detection-element infrared detector of meteorological satellite

By employing principal component analysis and standardization methods, the consistency problem among detectors in large-array multi-detector infrared detectors of meteorological satellites was solved, achieving efficient and accurate detector consistency detection and improving the reliability and application value of the data.

CN121595041APending Publication Date: 2026-03-03EARTH SYST NUMERICAL PREDICTION CENT OF CHINA METEOROLOGICAL ADMINISTRATION
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Patent Information

Application Number
CN202511870347.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-12
Publication Date
2026-03-03

AI Technical Summary

Technical Problem

Existing technologies in large-array multi-element infrared detectors for meteorological satellites suffer from systematic biases and non-uniform responses between elements, leading to inconsistent data and affecting observation accuracy and reliability. This limits their application, especially in high-precision data assimilation and extreme weather monitoring.

Method used

By employing principal component analysis (PCA) combined with standardization, a sample set is constructed by acquiring the brightness temperature data of the infrared detector, and then grouped, statistically analyzed, and standardized to identify anomalous detector elements and improve the efficiency and accuracy of detector element consistency detection.

Benefits of technology

By utilizing real observation data in a short period of time, it can accurately characterize the performance of detectors, improve the efficiency and accuracy of detector consistency detection, adapt to various satellite data, have strong scalability, and reduce the demand for manpower and material resources and additional errors.

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Abstract

The invention discloses a meteorological satellite large-array multi-probe infrared detector probe consistency detection method, which comprises the following steps: acquiring actual observation brightness temperature data of a meteorological satellite satellite-borne infrared detector, respectively carrying out quality control on observation data of a long wave band and a medium wave band, and constructing a sample set for consistency detection; carrying out principal component analysis on the sample set, extracting first k principal component components, and carrying out grouping statistics and standardization processing on the principal component components according to probe elements to obtain a standardized statistical magnitude of each probe element; and based on the standardized statistics, selecting the standardized statistics corresponding to the first 12 principal components for visual presentation, and identifying the abnormal probe element by analyzing a visual result. According to the method, principal component analysis is carried out on real observation data in combination with standardization processing, sufficient samples which are uniformly distributed are accumulated in a short time, the statistical result is high in representativeness and free of additional errors, and the real performance of a probe can be accurately represented.
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