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Sliding Window Filtering for Ground Moving Targets with Cross-Correlated Sensor Noises

  • 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 : 2019.05.23
  • Accepted : 2019.05.29
  • Published : 2019.05.31

Abstract

This paper reports a sliding window filtering approach for ground moving targets with cross-correlated sensor noise and uncertainty. In addition, the effect of uncertain parameters during a tracking error on the model performance is considered. A distributed fusion sliding window filter is also proposed. The distributed fusion filtering algorithm represents the optimal linear combination of local filters under the minimum mean-square error criterion. The derivation of the error cross-covariances between the local sliding window filters is the key to the proposed method. Simulation results of the motion of the ground moving target a demonstrate high accuracy and computational efficiency of the distributed fusion sliding window filter.

Keywords

HSSHBT_2019_v28n3_146_f0001.png 이미지

Fig. 1. The y-position error χ2,t and its estimates using CFSWF, DFSWF, CKF, and DKF.

HSSHBT_2019_v28n3_146_f0002.png 이미지

Fig. 2. MSE comparison for χ2,t with uncertainty δt = 1

HSSHBT_2019_v28n3_146_f0003.png 이미지

Fig. 3. MSE comparison for χ2,t without uncertainty δt = 0

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