• Title/Summary/Keyword: Probability of Kill

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Extended Target State Vector Estimation using AKF (적응형 칼만 필터를 이용한 확장 표적의 상태벡터 추정 기법)

  • Cho, Doo-Hyun;Choi, Han-Lim;Lee, Jin-Ik;Jeong, Ki-Hwan;Go, Il-Seok
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.43 no.6
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    • pp.507-515
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    • 2015
  • This paper proposes a filtering method for effective state vector estimation of highly maneuvering target. It is needed to hit the point called 'sweet spot' to increase the kill probability in missile interception. In paper, a filtering method estimates the length of a moving target tracked by a frequency modulated continuous wave (FMCW) radar. High resolution range profiles (HRRPs) is generated from the radar echo signal and then it's integrated into proposed filtering method. To simulate the radar measurement which is close to real, the study on the properties of scattering point of the missile-like target has been conducted with ISAR image for different angle. Also, it is hard to track the target efficiently with existing Kalman filters which has fixed measurement noise covariance matrix R. Therefore the proposed method continuously updates the covariance matrix R with sensor measurements and tracks the target. Numerical simulations on the proposed method shows reliable results under reasonable assumptions on the missile interception scenario.