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Multiple-Point Temperature Gradient Algorithm for Ring Laser Gyroscope Bias Compensation.

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  • 1College of Opto-electrics Science and Engineering, National University of Defense Technology, Changsha 410073, China. lg_163@163.com.

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|December 4, 2015
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Summary
This summary is machine-generated.

This study introduces a new algorithm to improve ring laser gyroscope (RLG) bias stability by compensating for temperature variations. The method enhances RLG precision and generalizability using a multiple-point temperature gradient approach.

Keywords:
error compensationgradient methodsparticle swarm optimizationring laser gyroscopesupport vector machinetemperature measurementtemperature sensors

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Area of Science:

  • Instrumentation and Measurement
  • Control Systems Engineering
  • Optical Engineering

Background:

  • Ring laser gyroscopes (RLGs) are critical for inertial navigation but suffer from bias instability.
  • Temperature fluctuations significantly impact RLG performance and accuracy.
  • Existing bias compensation methods have limitations in addressing complex thermal gradients.

Purpose of the Study:

  • To develop and validate a novel multiple-point temperature gradient algorithm for RLG bias compensation.
  • To enhance the bias stability and precision of RLGs under varying thermal conditions.
  • To optimize the selection of temperature sensor locations for improved RLG modeling.

Main Methods:

  • Implementation of a multiple-point temperature measurement system to create a thermo-image of the RLG block.
  • Utilizing particle swarm optimization to tune support vector machine (SVM) parameters for bias compensation.
  • Investigating an optimized design for thermometer placement to capture critical temperature gradients.

Main Results:

  • The proposed algorithm successfully compensates for RLG bias drift caused by temperature gradients.
  • Experimental results demonstrate a significant improvement in RLG bias stability compared to conventional methods.
  • The thermo-image and gradient analysis provide a more comprehensive understanding of RLG thermal behavior.

Conclusions:

  • The multiple-point temperature gradient algorithm offers a superior approach to RLG bias compensation.
  • The method enhances the precision and generalizability of RLG bias compensation models.
  • This technique is crucial for advancing the performance of inertial navigation systems reliant on RLGs.