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Coarse Alignment Technology on Moving base for SINS Based on the Improved Quaternion Filter Algorithm.

Tao Zhang1,2, Yongyun Zhu3,4, Feng Zhou5,6

  • 1School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China. 101011356@seu.edu.cn.

Sensors (Basel, Switzerland)
|June 21, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces an improved quaternion filter for faster initial alignment of strapdown inertial navigation systems (SINS). The enhanced algorithm achieves quicker convergence while maintaining accuracy, validated by turntable and vehicle tests.

Keywords:
Doppler velocity log (DVL)coarse alignmentimproved quaternion filter algorithmstrapdown inertial navigation system (SINS)

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Area of Science:

  • Navigation Systems
  • Control Theory
  • Signal Processing

Background:

  • Strapdown Inertial Navigation Systems (SINS) require accurate initial attitude determination for navigation.
  • Traditional quaternion filter algorithms offer high accuracy but suffer from slow convergence rates during initial alignment.
  • The need for faster and accurate initial alignment is critical in dynamic navigation applications.

Purpose of the Study:

  • To develop an improved quaternion filter algorithm for accelerated initial alignment of SINS.
  • To enhance the convergence speed of the quaternion filter without compromising alignment accuracy.
  • To validate the proposed algorithm's performance through experimental testing.

Main Methods:

  • Proposed an improved quaternion filter algorithm based on the error model of traditional quaternion filters.
  • Constructed a K matrix using the optimal quaternion algorithm principle.
  • Rebuilt the measurement model to incorporate acceleration and velocity errors, utilizing Doppler Velocity Log (DVL) for reference velocity.

Main Results:

  • The improved quaternion filter algorithm demonstrated a significantly faster convergence rate compared to the traditional quaternion filter.
  • Experimental results from turntable and vehicle tests confirmed the enhanced convergence speed.
  • The algorithm proved effective, correct, and practical for real-world SINS initial alignment.

Conclusions:

  • The improved quaternion filter algorithm successfully accelerates the initial alignment process for SINS.
  • The method offers a practical solution for achieving faster and accurate attitude determination.
  • This advancement is beneficial for applications requiring rapid SINS initialization.