A Coarse-Alignment Method Based on the Optimal-REQUEST Algorithm.

Area of Science:

• Navigation Systems
• Inertial Navigation
• Attitude Determination

Background:

• Strapdown inertial navigation systems (SINS) require accurate coarse alignment.
• Noise in observation vectors from inertial sensors degrades alignment accuracy and convergence.
• Traditional attitude determination methods face limitations in speed and accuracy due to noise.

Purpose of the Study:

• To propose a novel coarse-alignment method for SINS based on attitude determination.
• To address the limitations of existing methods by reducing noise impact on alignment.
• To enhance the convergence rate and accuracy of the coarse alignment process.

Main Methods:

• Developed an optimal attitude determination method named optimal-REQUEST.
• Utilized observation vectors from inertial sensors for attitude determination.
• Implemented an iterative method for determining the attitude quaternion and autonomously tuned filtering gain.

Main Results:

• The optimal-REQUEST algorithm demonstrated a faster convergence rate compared to traditional methods.
• Enhanced stability in coarse alignment was observed with the proposed method.
• Simulation and turntable tests validated the superior performance of the optimal-REQUEST algorithm.

Conclusions:

• The proposed optimal-REQUEST method offers significant improvements in convergence speed and alignment stability for SINS.
• Autonomous tuning of filtering gain contributes to faster and more accurate attitude determination.
• The method shows high applicability for practical navigation system implementations.