• Title/Summary/Keyword: Multiple Probabilistic Data Association Filter(MPDAF)

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Multiple PDAF Algorithm for Estimation States Multiple of the Ships (다중 선박의 상태추정을 위한 Multiple PDAF 알고리즘)

  • Jaeha Choi;Jeonghong Park;Minju Kang;Hyejin Kim;Wonkeun Youn
    • Journal of the Society of Naval Architects of Korea
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    • v.60 no.4
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    • pp.248-255
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    • 2023
  • In order to implement the autonomous navigation function, it is essential to track an object within a certain radius of the ship's route. This paper proposes the Multiple Probabilistic Data Association Filter (MPDAF), which can track multiple ships by extending Probabilistic Data Association Filter (PDAF), an existing single object tracking algorithm, using radar data obtained from real marine environments. The proposed MPDAF algorithm was developed to address the problem of tracking multiple objects in a complex environment where there can be significant uncertainty in the number and identification of objects to be tracked. Using real-world radar data provided by the German aerospace center (DLR), it has been verified that the proposed algorithm can track a large number of objects with a small position error.