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A Coarse Alignment Method Based on Digital Filters and Reconstructed Observation Vectors.

Xiang Xu1,2, Xiaosu Xu3,4, Tao Zhang5,6

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Summary

This study introduces a new coarse alignment method for strapdown inertial navigation systems (SINS) using apparent gravity. The method effectively filters noise and handles vehicle maneuvers for improved navigation accuracy in moving conditions.

Keywords:
SINScoarse alignmentdigital filterrobust Kalman filtervector reconstruction

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Area of Science:

  • Navigation Systems
  • Geophysics
  • Signal Processing

Background:

  • Strapdown Inertial Navigation Systems (SINS) require accurate initial alignment.
  • Apparent gravitational motion is a key factor in SINS alignment.
  • Complex operating conditions introduce noise and outliers in sensor measurements.

Purpose of the Study:

  • To propose a novel coarse alignment method for SINS based on apparent gravitational motion.
  • To address challenges posed by measurement noise and vehicle maneuvers.
  • To enhance the accuracy and robustness of SINS alignment.

Main Methods:

  • Developed a coarse alignment method utilizing apparent gravitational motion.
  • Designed a low-pass digital filter to eliminate high-frequency noise from observation vectors.
  • Implemented a parameter recognition and vector reconstruction method with an adaptive Kalman filter.
  • Introduced a robust filter based on Huber's M-estimation theory to handle outliers.

Main Results:

  • The proposed method effectively filters measurement noise and reconstructs accurate observation vectors.
  • An adaptive Kalman filter successfully estimates unknown parameters for vector reconstruction.
  • Huber's M-estimation based robust filter mitigates the impact of outliers during vehicle maneuvers.
  • Experimental results validate the method's performance in both simulation and physical tests.

Conclusions:

  • The proposed coarse alignment method demonstrates equivalence to the apparent velocity method in swaying motion.
  • The method significantly outperforms existing techniques in moving mode for self-contained SINS.
  • This approach offers a robust and accurate solution for SINS coarse alignment under challenging conditions.