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Position observation-based calibration method for an LDV/SINS integrated navigation system.

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    A new robust calibration method enhances laser Doppler velocimeter (LDV) and strapdown inertial navigation system (SINS) integration for precise navigation. This GNSS-aided approach improves accuracy even with noisy data, reducing dead reckoning errors.

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    Area of Science:

    • Navigation Systems Engineering
    • Sensor Fusion
    • Metrology

    Background:

    • Laser Doppler Velocimeters (LDV) offer high accuracy and fast response for navigation.
    • Integrating LDV with Strapdown Inertial Navigation Systems (SINS) promises enhanced precision.
    • Existing calibration methods for LDV/SINS are sensitive to measurement noise and outliers.

    Purpose of the Study:

    • To develop a robust calibration method for LDV/SINS integrated navigation systems.
    • To address limitations of current calibration techniques, particularly their sensitivity to noisy GNSS data.
    • To improve the accuracy of navigation systems that combine LDV and SINS.

    Main Methods:

    • A novel GNSS-aided calibration method based on position observation is proposed.
    • Utilizes attitude information from an adaptive Kalman filter in the GNSS/SINS system.
    • Constructs an observation vector using LDV velocity, GNSS position, and system attitude.
    • Employs ratio of observation vector modulus and Davenport's q-method for error determination.

    Main Results:

    • The proposed method accurately determines LDV scale factor error and misalignment angles.
    • Verified through vehicle tests with both clean and outlier-corrupted GNSS signals.
    • Achieved horizontal position errors of less than 0.0314% and 0.1033% of mileage in tests.

    Conclusions:

    • The developed GNSS-aided calibration method is robust and accurate for LDV/SINS integration.
    • Demonstrates superior performance compared to existing methods, especially under noisy conditions.
    • Significantly improves the dead reckoning accuracy of integrated navigation systems.