Model Switching Detection-Aided Adaptive Transition Probability Matrix IMM Algorithm

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

Abstract

In conventional interactive multiple model (IMM) algorithm, the fixed transition probability matrix results in slow model switching and low tracking accuracy. Existing adaptive transition probability IMM algorithms still suffer from large errors during model switching. This paper proposes a model switching detection-aided adaptive transition probability matrix IMM algorithm. To deal with model switch time delay, a transition probability correction function is established, capable of dynamically and rapidly adjusting the transition probabilities. And a model switching detection method is proposed to improve tracking accuracy during model switching. By the numerical simulation, the method's efficacy is substantiated and confirmed.

Original languageEnglish
Title of host publicationIEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331515669
DOIs
Publication statusPublished - 2024
Event2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024 - Zhuhai, China
Duration: 22 Nov 202424 Nov 2024

Publication series

NameIEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024

Conference

Conference2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024
Country/TerritoryChina
CityZhuhai
Period22/11/2424/11/24

Keywords

  • Adaptive Transition Probability Matrix
  • IMM
  • Model Switching Detection

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