Nonlinear Tracking Using Uncorrelated Conversion Based Continuous-Discrete Filter

Haibo Yang, Dongmei Jiang, Yu Zhu

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

Abstract

For the strong nonlinear continuous-discrete tracking problem, A novel method has been proposed, which is square root continuous-discrete cubature Kalman filter based uncorrelated conversion. We construct uncorrelated conversion function and perform uncorrelated conversion on measurements. The square root continuous-discrete cubature Kalman filter is updated with the measurements and its uncorrelated conversion. The performance of the filter is improved due to gain of uncorrelated conversion. Finally, the performance of the new method was verified to be excellent compared with current methods in the classical tracking scenario.

Original languageEnglish
Title of host publicationProceedings of 2024 IEEE International Conference on Unmanned Systems, ICUS 2024
EditorsRong Song
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages915-920
Number of pages6
ISBN (Electronic)9798350384185
DOIs
StatePublished - 2024
Event2024 IEEE International Conference on Unmanned Systems, ICUS 2024 - Nanjing, China
Duration: 18 Oct 202420 Oct 2024

Publication series

NameProceedings of 2024 IEEE International Conference on Unmanned Systems, ICUS 2024

Conference

Conference2024 IEEE International Conference on Unmanned Systems, ICUS 2024
Country/TerritoryChina
CityNanjing
Period18/10/2420/10/24

Keywords

  • continuous-discrete
  • nonlinear tracking
  • uncorrelated conversion

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