Coarse Alignment Technology on Moving base for SINS Based on the Improved Quaternion Filter Algorithm

Area of Science:

• Navigation Systems
• Control Theory
• Signal Processing

Background:

• Strapdown Inertial Navigation Systems (SINS) require accurate initial attitude determination for navigation.
• Traditional quaternion filter algorithms offer high accuracy but suffer from slow convergence rates during initial alignment.
• The need for faster and accurate initial alignment is critical in dynamic navigation applications.

Purpose of the Study:

• To develop an improved quaternion filter algorithm for accelerated initial alignment of SINS.
• To enhance the convergence speed of the quaternion filter without compromising alignment accuracy.
• To validate the proposed algorithm's performance through experimental testing.

Main Methods:

• Proposed an improved quaternion filter algorithm based on the error model of traditional quaternion filters.
• Constructed a K matrix using the optimal quaternion algorithm principle.
• Rebuilt the measurement model to incorporate acceleration and velocity errors, utilizing Doppler Velocity Log (DVL) for reference velocity.

Main Results:

• The improved quaternion filter algorithm demonstrated a significantly faster convergence rate compared to the traditional quaternion filter.
• Experimental results from turntable and vehicle tests confirmed the enhanced convergence speed.
• The algorithm proved effective, correct, and practical for real-world SINS initial alignment.

Conclusions:

• The improved quaternion filter algorithm successfully accelerates the initial alignment process for SINS.
• The method offers a practical solution for achieving faster and accurate attitude determination.
• This advancement is beneficial for applications requiring rapid SINS initialization.