Improved Multistage In-Motion Attitude Determination Alignment Method for Strapdown Inertial Navigation System.

Area of Science:

• Aerospace Engineering
• Navigation Systems
• Geophysics

Background:

• Traditional in-motion attitude determination alignment (IMADA) methods for strapdown inertial navigation systems suffer from model and calculation errors, particularly when aided by velocity measurements.
• Existing Vb-aided IMADA techniques exhibit degradation in alignment accuracy, especially during high-level alignment stages and with varying vehicle velocities.

Purpose of the Study:

• To develop an improved multistage IMADA algorithm that overcomes the limitations of traditional methods.
• To enhance the robustness and accuracy of in-motion alignment for strapdown inertial navigation systems.

Main Methods:

• Integration of traditional IMADA, a novel dual velocity-modeling IMADA, and a multiple repeated alignment process.
• Addressing principled model errors and calculation errors inherent in traditional Vb-aided IMADA.

Main Results:

• Significant reduction in heading degradation during second-level alignment (from 20 to 10 instances).
• A 23% improvement in heading alignment accuracy was achieved.
• Consistent heading alignment accuracy (1.3063° to 1.3564°) observed across different vehicle speeds (20 m/s, 60 m/s, 80 m/s).

Conclusions:

• The proposed algorithm effectively resolves drawbacks of traditional Vb-based IMADA.
• The enhanced IMADA largely mitigates alignment degradation phenomena and removes velocity-dependent accuracy degradation.
• Experimental validation through car-mounted and Monte Carlo simulations confirms the algorithm's effectiveness.