An Improved Alignment Method for the Strapdown Inertial Navigation System (SINS).

Area of Science:

• Navigation Systems
• Control Theory
• Geophysics

Background:

• Strapdown inertial navigation systems (SINS) require accurate initial alignment for precise positioning.
• Traditional local-level mechanization methods face challenges with linear movement errors affecting heading accuracy.
• Existing Kalman filter (KF) based alignment techniques can be sensitive to initial alignment accuracy and prone to oscillations.

Purpose of the Study:

• To develop an innovative inertial navigation system (INS) mechanization and Kalman filter (KF) algorithm for fine alignment of SINS on stationary bases.
• To improve system reliability and decrease total alignment time by requiring lower coarse alignment accuracy.
• To enhance closed-loop KF stability by reducing oscillations caused by system errors.

Main Methods:

• Development of an improved INS mechanization in a pseudo-geographic frame, rebuilt based on initial position.
• Decoupling of linear movement errors to eliminate their effect on heading accuracy.
• Application of open-loop and closed-loop Kalman filters with the proposed mechanization.

Main Results:

• The new mechanization effectively eliminates heading errors caused by linear movements.
• The proposed algorithm demonstrates superior performance in both simulations and experiments compared to traditional methods.
• Reduced coarse alignment accuracy requirements lead to improved system reliability and shorter alignment times.

Conclusions:

• The developed pseudo-geographic frame mechanization offers significant advantages over traditional local-level methods for SINS alignment.
• The proposed algorithm enhances SINS alignment by improving stability, reducing alignment duration, and increasing reliability.
• The method is versatile and applicable to polar alignment scenarios, validated through rigorous testing.