• Title/Summary/Keyword: GA-based IKF

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A DNA Coding-Based Intelligent Kalman Filter for Tracking a Maneuvering Target (기동표적 추적을 위한 DNA 코딩 기반 지능형 칼만 필터)

  • Lee, Bum-Jik;Joo, Young-Hoon;Park, Jin-Bae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.2
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    • pp.131-136
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    • 2003
  • The problem of maneuvering target tracking has been studied in the field of the state estimation over decades. The Kalman filter has been widely used to estimate the states of the target, but in the presence of a maneuver, its performance may be seriously degraded. In this paper, to solve this problem and track a maneuvering target effectively, DNA coding-based intelligent Kalman filter (DNA coding-based IKF) is proposed. The proposed method can overcome the mathematical limits of conventional methods and can effectively track a maneuvering target with only one filter by using the fuzzy logic based on DNA coding method. The tracking performance of the proposed method is compared with those of the adaptive interacting multiple model (AIMM) method and the GA-based IKF in computer simulations.

DNA Coding-Based Intelligent Kalman Filter for Tracking a Maneuvering Target (기동표적 추적을 위한 DNA 코딩 기반 지능형 칼만 필터)

  • 이범직;주영훈;박진배
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2002.12a
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    • pp.118-121
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    • 2002
  • The problem of maneuvering target tracking has been studied in the field of the state estimation over decades. The Kalman filter has been widely used to estimate the state of the target, but in the presence of a maneuver, its performance may be seliously degraded. In this paper, to solve this problem and track a maneuvering target effectively, DNA coding-based intelligent Kalman filter (DNA coding-based IKF) is proposed. The proposed method can overcome the mathematical limits of conventional methods and can effectively track a maneuvering target with only one filter by using the fuzzy logic based on DNA coding method. The tracking performance of the proposed method is compared with those of the adaptive interacting multiple model (AIMM) method and the GA-based IKF in computer simulations.