Research of INS/CNS/SMN Adaptive Integrated Navigation Algorithm for Sea Area

Zhaoxu Tian, Yongmei Cheng, Nan Liu, Shun Yao, Weijin Bai, Ruowang Zhuang, Li Dai

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

Abstract

In this paper, a novel INS/CNS/SMN adaptive integrated navigation algorithm is proposed for long term and high precision navigation in sea area. The structure of INS/CNS/SMN integrated navigation system is established in the algorithm. The cloud and fog model in the Nanhai Sea area is constructed for CNS availability. The three types of sea area landmarks are defined, and the corresponding matching methods and strategies of these landmarks are given. At the same time, an automatic classification model of sea area landmarks based on SVM is also designed. The INS/CNS/SMN adaptive integrated navigation algorithm in sea area is simulated and verified in different altitudes and trajectories. The results show that CNS and SMN can adaptively help INS for long term and high precision navigation.

Original languageEnglish
Title of host publicationProceedings of the 40th Chinese Control Conference, CCC 2021
EditorsChen Peng, Jian Sun
PublisherIEEE Computer Society
Pages3368-3373
Number of pages6
ISBN (Electronic)9789881563804
DOIs
StatePublished - 26 Jul 2021
Event40th Chinese Control Conference, CCC 2021 - Shanghai, China
Duration: 26 Jul 202128 Jul 2021

Publication series

NameChinese Control Conference, CCC
Volume2021-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference40th Chinese Control Conference, CCC 2021
Country/TerritoryChina
CityShanghai
Period26/07/2128/07/21

Keywords

  • automatic classification model
  • cloud and fog model
  • Integrated navigation
  • sea area landmarks

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