Inaccurate measurement of the lever arm between IMU (Inertial Measurement Unit) and GNSS (Global Navigation Satellite System) antennas is a common source of error in GNSS/INS integrated navigation systems. This error significantly affects the accuracy of integrated navigation under dynamic conditions, especially during rotational motion. Usually, the following methods are used to compensate for the errors in the integrated navigation system caused by the influence of the lever arm.
1. Offline Calibration: Before the system is put into use, the lever arm vector is accurately estimated through specific testing maneuvers. Usually, static multi position method and dynamic maneuver method ("8" or snake maneuver) are used. If the maneuvering design is appropriate and the data quality is high, very accurate estimates of the lever arm can be obtained.
2. Online Estimation: During the operation of a integrated navigation filter (usually a Kalman filter or its variants such as EKF, UKF), the lever arm vector is used as part of the state variable for real-time estimation. It does not require additional offline testing and can gradually correct lever arm errors during normal system operation.
3. Adaptive/Robust Filtering: When the arm error cannot be accurately known and the online estimation effect is poor (such as insufficient carrier mobility), adjusting the filter parameters can tolerate or weaken the influence of arm error, prevent filter divergence, or provide overly optimistic accuracy evaluation.
It is recommended to prioritize offline calibration. If conditions permit, conducting specialized dynamic maneuvering calibration is the best method to obtain high-precision lever arm values. Secondly, online estimation is implemented to estimate the lever arm vector as a state variable in the integrated navigation filter. This is the most commonly used and effective real-time processing method in engineering practice. Be sure to ensure that the carrier has sufficient rotational maneuverability to make the lever arm observable. Finally, combining adaptive/robust strategies to prevent severe performance degradation or divergence.
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