IMM Algorithm Using Intelligent Input Estimation for Maneuvering Target Tracking(Systems and Control)

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概要

• 論文の詳細を見る

• 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.

• 社団法人電子情報通信学会の論文
• 2005-05-01

著者

• PARK Jin

  Dept. of Electrical and Electronic Eng., Yonsei University

• Lee Bum

  R.o.k. Navy And Also With Naval Combat System Div. Agency For Defense Development

• JOO Young

  School of Electronic and Information Eng., Kunsan University

• Park Jin

  Dept. Of Electrical And Electronic Eng. Yonsei University

関連論文

• Robust Extended Kalman Filtering via Krein Space Estimation (Systems and Control)
• IMM Algorithm Using Intelligent Input Estimation for Maneuvering Target Tracking(Systems and Control)

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