Analytical quaternion-based bias estimation algorithm for fast and accurate stationary gyro-compassing

Area of Science:

• Navigation Systems
• Inertial Navigation
• Geodesy

Background:

• Strapdown Inertial Navigation Systems (SINS) require precise alignment for accurate positioning.
• Traditional recursive alignment methods, such as Kalman filtering, can be computationally intensive and slow to converge, especially for azimuth angle estimation.
• Existing alignment techniques often demand considerable time, particularly in stationary conditions.

Purpose of the Study:

• To develop a novel, non-recursive approach for SINS alignment that accelerates bias error calculation.
• To improve the speed of SINS alignment without compromising accuracy compared to traditional methods.
• To overcome the slow convergence limitations of recursive algorithms in SINS alignment.

Main Methods:

• Utilized quaternion-based analytical relationships for expedited bias error calculations.
• Developed a methodology distinct from conventional recursive filtering techniques.
• Employed simulations and experimental validation to assess performance.

Main Results:

• The proposed approach significantly reduces alignment time, achieving comparable accuracy to traditional fine alignment methods within 20 seconds.
• Demonstrated a substantial improvement over traditional methods that require approximately 10 minutes for azimuth angle estimation in stationary conditions.
• Validated the effectiveness of quaternion-based analytical relationships in bypassing slow convergence behaviors.

Conclusions:

• The novel SINS alignment method offers a faster and accurate alternative to traditional recursive approaches.
• The technique is particularly advantageous for applications requiring rapid alignment in stationary environments.
• Future work may explore extending applicability to dynamic conditions and evaluating performance with different grades of Inertial Measurement Units (IMUs).