IMM algorithm using intelligent input estimation for maneuvering target tracking

Bum Jik Lee, Jin Bae Park, Young Hoon Joo

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


A new interacting multiple model (IMM) algorithm using intelligent input estimation (IIE) is proposed for maneuvering target tracking. In the proposed method, the acceleration level for each sub-model is determined by IIE-the estimation of the unknown target acceleration by a fuzzy system using the relation between the residuals of the maneuvering filter and the non-maneuvering filter. The genetic algorithm (GA) is utilized to optimize a fuzzy system for a sub-model within a fixed range of target acceleration. Then, multiple models are represented as the acceleration levels estimated by these fuzzy systems, which are optimized for different ranges of target acceleration. In computer simulation for an incoming anti-ship missile, it is shown that the proposed method has better tracking performance compared with the adaptive interacting multiple model (AIMM) algorithm.

Original languageEnglish
Pages (from-to)1320-1327
Number of pages8
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Issue number5
Publication statusPublished - 2005

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering
  • Applied Mathematics


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