A Novel Alignment Method for SINS with Large Misalignment Angles Based on EKF2 and AFIS.

Area of Science:

• Navigation Systems Engineering
• Control Theory
• Signal Processing

Background:

• Strapdown inertial navigation systems (SINS) require precise initial alignment, which is challenging under large initial misalignment angles.
• Traditional alignment methods struggle with convergence and accuracy when initial attitude errors are significant.

Purpose of the Study:

• To propose a novel filtering alignment method for SINS that effectively handles large initial misalignment angles.
• To enhance the accuracy and convergence speed of SINS alignment using advanced filtering techniques.

Main Methods:

• A second-order nonlinear state equation is formulated using quaternion representation for attitude errors and incorporating nonlinear velocity and attitude error models.
• A linear measurement equation is derived from SINS velocity outputs.
• A filtering scheme is designed by integrating the second-order extended Kalman filter (EKF2) with an adaptive fuzzy inference system (AFIS) to adjust the covariance matrix Pk/k-1.

Main Results:

• Monte Carlo simulations demonstrate rapid convergence of pitch, roll, and yaw misalignment errors to approximately 14″, 15″, and 7.62' within 350 seconds, even with initial errors ranging from -40° to 40° (pitch/roll) and -50° to 50° (yaw).
• The method shows robust convergence even with extremely large initial misalignment angles (e.g., 80°, 120°, 170°), attributed to the AFIS's adaptive covariance matrix adjustment.
• Turntable experiments validated the proposed method's effectiveness and superiority over other nonlinear alignment techniques.

Conclusions:

• The proposed EKF2 and AFIS-based filtering alignment method offers a robust and accurate solution for SINS alignment under significant initial misalignment conditions.
• The adaptive capability of the fuzzy inference system is crucial for maintaining convergence and accuracy in challenging alignment scenarios.
• This advanced alignment technique holds significant promise for improving the performance of navigation systems in various applications.