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A robust self-alignment method for ship's strapdown INS under mooring conditions.

Feng Sun1, Haiyu Lan, Chunyang Yu

  • 1Marine Navigation Research Institute, College of Automation, Harbin Engineering University, Harbin 150001, China. sunfeng407@126.com

Sensors (Basel, Switzerland)
|June 27, 2013
PubMed
Summary

This study introduces a robust method for aligning strapdown inertial navigation systems (INS) on ships, even in challenging sea conditions. The novel approach enhances accuracy and speed by effectively reducing sensor noise and external disturbances.

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Area of Science:

  • Navigation Systems
  • Signal Processing
  • Marine Engineering

Background:

  • Strapdown inertial navigation systems (INS) require precise initial alignment using gravity and Earth's rotation.
  • Shipboard INS face significant challenges during mooring due to sensor noise and sea-induced disturbances, hindering accurate alignment.
  • Conventional alignment methods struggle to achieve rapid and precise results under these adverse conditions.

Purpose of the Study:

  • To develop a robust and accurate self-alignment method for shipboard strapdown INS under mooring conditions.
  • To mitigate the effects of both low-frequency and high-frequency disturbances on INS alignment accuracy.
  • To introduce a novel prefiltering technique for enhancing the performance of INS alignment.

Main Methods:

  • Utilized an inertial frame-based alignment method to adapt to mooring conditions and filter low-frequency disturbances through integration and averaging.
  • Proposed a novel Hidden Markov Model based Kalman Filter (HMM-KF) to effectively remove high-frequency error components without introducing time delays.
  • Conducted turntable, mooring, and sea experiments to validate the proposed alignment method and the HMM-KF prefilter.

Main Results:

  • The inertial frame-based alignment effectively removed periodical low-frequency external disturbance components.
  • The HMM-KF prefilter successfully eliminated high-frequency error components with minimal time delay.
  • Experimental results demonstrated the rapidness and accuracy of the proposed self-alignment method.

Conclusions:

  • The proposed inertial frame-based alignment method combined with the HMM-KF prefilter offers a robust solution for shipboard INS alignment under mooring conditions.
  • The method significantly improves alignment speed and accuracy by effectively denoising sensor measurements.
  • The HMM-KF demonstrates excellent performance in removing high-frequency noise without causing detrimental time delays, validating its suitability for dynamic navigation applications.