A Characteristic Parameter Matching Algorithm for Gravity-Aided Navigation of Underwater Vehicles

Bo Wang*, Jingwei Zhu, Zhihong Deng, Mengyin Fu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

36 Citations (Scopus)

Abstract

The gravity matching algorithm is a key of the gravity-aided inertial navigation system (INS). The traditional matching algorithm connects only the measured gravity anomaly data to the position of the carrier according to a certain method to correct the inertial error. The gravitational field characteristic parameters should also be considered in the matching algorithm to improve the matching accuracy and reduce the number of mismatching. Therefore, based on the vector matching algorithm, a characteristic parameter matching algorithm is proposed. This paper presents new methods to calculate the characteristic parameters and the range of particle filters to increase the accuracy of matching. The gravity anomaly value of each particle is calculated more accurately by the proposed method of continuous gravity anomaly. Due to the high short-time accuracy of inertial navigation, the final trajectory is obtained by rigid transformation of a series of positions indicated by the INS corresponding to the trajectory. Simulation results prove that when compared with the vector matching algorithm, the proposed method makes the matching results more accurate and more reliable.

Original languageEnglish
Article number8352025
Pages (from-to)1203-1212
Number of pages10
JournalIEEE Transactions on Industrial Electronics
Volume66
Issue number2
DOIs
Publication statusPublished - Feb 2019

Keywords

  • Gravity-aided navigation
  • matching algorithm
  • underwater vehicles

Fingerprint

Dive into the research topics of 'A Characteristic Parameter Matching Algorithm for Gravity-Aided Navigation of Underwater Vehicles'. Together they form a unique fingerprint.

Cite this