Journal of Sensor Science and Technology (센서학회지)

The Korean Sensors Society (한국센서학회)
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A Finite Memory Filter for Discrete-Time Stochastic Linear Delay Systems

  • Song, Il Young (Department of Sensor Systems, Hanwha Corporation Defense R&D Center) ;
  • Song, Jin Mo (Department of Sensor Systems, Hanwha Corporation Defense R&D Center) ;
  • Jeong, Woong Ji (Department of Sensor Systems, Hanwha Corporation Defense R&D Center) ;
  • Gong, Myoung Sool (Department of Sensor Systems, Hanwha Corporation Defense R&D Center)
  • Received : 2019.07.15
  • Accepted : 2019.07.30
  • Published : 2019.07.31
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Abstract

In this paper, we propose a finite memory filter (estimator) for discrete-time stochastic linear systems with delays in state and measurement. A novel filtering algorithm is designed based on finite memory strategies, to achieve high estimation accuracy and stability under parametric uncertainties. The new finite memory filter uses a set of recent observations with appropriately chosen initial horizon conditions. The key contribution is the derivation of Lyapunov-like equations for finite memory mean and covariance of system state with an arbitrary number of time delays. A numerical example demonstrates that the proposed algorithm is more robust and accurate than the Kalman filter against dynamic model uncertainties.

Keywords

HSSHBT_2019_v28n4_216_f0001.png 이미지

Fig. 1. MSEs comparison between KFTD and three FMKFTD

HSSHBT_2019_v28n4_216_f0002.png 이미지

Fig. 2. MSEs comparison between three FMKFTD and KFTD outside the TEUI

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