A novel adaptive filter for highly maneuvering target

Gaoru Xue, Yan Liang, Wenchao Zhan, Yanan Yong, Ping Qiao

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

1 Scopus citations

Abstract

This paper considers the highly maneuvering target tracking as a discrete-time stochastic system with generalized unknown disturbance input, which can represent an arbitrary linear combination of dynamic, random, and deterministic disturbance inputs. The proposed filter based on upper bound filter (UBF) can adaptively optimize adjust factor to find the globally optimal solution of covariance matrices of the state predictions, innovation and estimates. To reduce the linearization error, a iterative optimization frame is designed. The experiment on 'Smaneuver' of anti-ship missile shows that the proposed filter can significantly reduce the peak estimation errors due to maneuvers.

Original languageEnglish
Title of host publication2016 CIE International Conference on Radar, RADAR 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509048281
DOIs
StatePublished - 4 Oct 2017
Event2016 CIE International Conference on Radar, RADAR 2016 - Guangzhou, China
Duration: 10 Oct 201613 Oct 2016

Publication series

Name2016 CIE International Conference on Radar, RADAR 2016

Conference

Conference2016 CIE International Conference on Radar, RADAR 2016
Country/TerritoryChina
CityGuangzhou
Period10/10/1613/10/16

Keywords

  • Adaptively filter
  • Highly maneuvering target tracking
  • Iterative optimization
  • Stochastic system

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