日本航海学会論文集
Online ISSN : 2187-3275
Print ISSN : 0388-7405
ISSN-L : 0388-7405
離島定期船のGNSS観測データと航路データを用いた状態予測手法の提案と検証
大田 啓人浦上 美佐子
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ジャーナル 認証あり

2025 年 152 巻 p. 48-55

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We are aiming for predicting and imputation missing data when we use Kalman Filter for estimating vessel position. When dealing with a isolated island sea route like this one, the sampling interval for data acquisition may be long due to problems with equipment, etc. In this case, we would only use state extrapolation. In such case, when predicting the next position data, the accuracy of the prediction step alone will be greatly reduced if the sampling interval is long. Then, in this paper, we propose vessel position prediction method that uses sea route predefined for a vessel, and report on the improvement in the accuracy of position prediction under certain conditions.

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この記事はクリエイティブ・コモンズ [表示 - 非営利 - 改変禁止 4.0 国際]ライセンスの下に提供されています。
https://creativecommons.org/licenses/by-nc-nd/4.0/deed.ja
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