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On-orbit calibration approach for star cameras based on the iteration method with variable weights.

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    This study introduces an attitude-independent calibration method for star cameras, enhancing precision and reducing noise. The approach efficiently optimizes parameters and removes errors from misidentified stars using iterative weighting.

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    Area of Science:

    • Spacecraft instrumentation
    • Optical engineering
    • Photogrammetry

    Background:

    • Accurate on-orbit calibration of star cameras is crucial for spacecraft attitude determination.
    • Existing methods often struggle with parameter interactions and misidentified stars, impacting precision.
    • Global optimization and noise removal are key challenges in star camera calibration.

    Purpose of the Study:

    • To develop an efficient, attitude-independent calibration approach for star cameras.
    • To achieve one-step optimization of principal point, focal length, and focal plane distortion.
    • To enhance precision and robustness by addressing parameter interactions and star misidentification.

    Main Methods:

    • Developed an attitude-independent calibration approach using least-square estimation with multiple star images.
    • Implemented an iterative method with variable weights to eliminate the influence of misidentified star pairs.
    • Performed global optimization considering the interaction among star camera parameters.

    Main Results:

    • The approach enables simultaneous optimization of principal point, focal length, and high-order focal plane distortion.
    • Iterative weighting effectively removes the impact of misidentified star pairs, improving estimation precision.
    • The method requires fewer star images compared to traditional approaches.

    Conclusions:

    • The proposed attitude-independent calibration method is precise and robust for star cameras.
    • This approach offers significant improvements in efficiency and accuracy for on-orbit calibration.
    • The technique effectively handles complex interactions and potential errors in star imaging data.