A fuzzy pattern based ICCP matching algorithm in gravity-aided navigation

Liu Chunmei, Miao Lingjuan, Dai Tian

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

The gravity anomalies data has been introduced as a supplementary information to the Inertial Navigation Systems (INSs) to limit its inherent errors accumulated over time. The article mainly focuses on the improvement of iterative closest contour point(ICCP) algorithm commonly used in the gravity-aided inertial navigation system(GAINS). Dealing with the noise of gravimeter measurement data, the algorithm is generalized in the aspect of the accuracy and robustness by a kind of fuzzy pattern recognition technique which gives each sample point a special weight based on its noise size. To reduce the consumption of data sampling time, a simple point matching strategy is proposed. When the system gets a new point, it would be the last one of the next matching line while the first point of the current matching line would be abandoned. The simulation proves that the generalization of the algorithm could achieve high accuracy and timeliness to meet the requirement of AUVs navigation.

Original languageEnglish
Title of host publicationProceedings of the 2017 6th International Conference on Network, Communication and Computing, ICNCC 2017
PublisherAssociation for Computing Machinery
Pages54-58
Number of pages5
ISBN (Electronic)9781450353663
DOIs
Publication statusPublished - 8 Dec 2017
Event6th International Conference on Network, Communication and Computing, ICNCC 2017 - Kunming, China
Duration: 8 Dec 201710 Dec 2017

Publication series

NameACM International Conference Proceeding Series

Conference

Conference6th International Conference on Network, Communication and Computing, ICNCC 2017
Country/TerritoryChina
CityKunming
Period8/12/1710/12/17

Keywords

  • Fuzzy pattern recognition
  • Gravity matching
  • ICCP algorithm
  • Inertial navigation
  • Real-time matching strategy

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