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An Improved Adaptive Compensation H∞ Filtering Method for the SINS' Transfer Alignment Under a Complex Dynamic

Weiwei Lyu1,2, Xianghong Cheng3,4, Jinling Wang5

  • 1School of Instrument Science & Engineering, Southeast University, Nanjing 210096, China. lvww0220@seu.edu.cn.

Sensors (Basel, Switzerland)
|January 24, 2019
PubMed
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This study introduces an adaptive H∞ filter to enhance transfer alignment accuracy in strapdown inertial navigation systems (SINS). The method improves both rapid alignment and navigation precision in challenging dynamic conditions.

Area of Science:

  • Navigation Systems
  • Control Theory
  • Signal Processing

Background:

  • Transfer alignment in strapdown inertial navigation systems (SINS) faces significant challenges in complex dynamic environments.
  • Existing methods struggle with rapidity and accuracy, particularly concerning sensor error compensation and filtering divergence.

Purpose of the Study:

  • To improve the rapidity and accuracy of transfer alignment for SINS.
  • To develop an enhanced adaptive compensation H∞ filtering method to suppress filtering divergence and calibrate sensor errors.

Main Methods:

  • Application of velocity plus attitude matching in the transfer alignment model.
  • Establishment of an error compensation model for online inertial sensor calibration.
  • Proposal and optimization of an improved adaptive compensation H∞ filtering method with a dynamically adjustable robustness factor.
Keywords:
adaptive compensationcomplex dynamic environmentfiltering divergencerobustness factorstrapdown inertial navigation system (SINS)transfer alignment

Related Experiment Videos

Main Results:

  • The proposed adaptive compensation H∞ filter effectively suppresses filtering divergence.
  • Aerial transfer alignment experiments demonstrate significant improvements in transfer alignment accuracy.
  • Enhanced pure inertial navigation accuracy was observed in complex dynamic environments.

Conclusions:

  • The adaptive compensation H∞ filtering method offers superior performance for transfer alignment in SINS.
  • The dynamic adjustment of the robustness factor enhances system accuracy and robustness.
  • The proposed method provides a viable solution for improving SINS performance under complex dynamic conditions.