Gaussian mixture approximation smoother for hypersonic glide reentry vehicles tracking

Wenchao Zhan, Yan Liang, Linfeng Xu, Ping Qiao, Liuqing Yang

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

Abstract

Tracking hypersonic glide reentry vehicles (HGRVs) is considered in the paper. Firstly, justified by an analysis of dynamic models of HGRVs, we proposed a more accurate motion model with less computation burden. Secondly, fixed-interval Gaussian mixture approximation smoother for non-linear Markov jump systems (NLMJSs) is presented in the paper. The Gaussian mixture filter can effectively approximate the state posterior PDF and the smoother can improve the estimation accuracy. Combining this two strategies, we presented a general framework to solve the problem of HGRVs tracking. Comparing with particle filter and Gaussian mixture approximation filter without smoothing, the proposed filter performs better with proper computation.

Original languageEnglish
Title of host publication20th International Conference on Information Fusion, Fusion 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9780996452700
DOIs
StatePublished - 11 Aug 2017
Event20th International Conference on Information Fusion, Fusion 2017 - Xi'an, China
Duration: 10 Jul 201713 Jul 2017

Publication series

Name20th International Conference on Information Fusion, Fusion 2017 - Proceedings

Conference

Conference20th International Conference on Information Fusion, Fusion 2017
Country/TerritoryChina
CityXi'an
Period10/07/1713/07/17

Keywords

  • Gaussian mixture approximation
  • hypersonic glide reentry vehicles
  • non-linear Markov jump systems
  • smoother

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