Ensemble and Fuzzy Kalman Filter for position estimation of an autonomous underwater vehicle based on dynamical system of AUV motion
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- 作者：Ngatinia ; ngatini10@mhs.matematika.its.ac.id" class="auth_mail" title="E-mail the corresponding author ; Erna Apriliania ; april@matematika.its.ac.id" class="auth_mail" title="E-mail the corresponding author ; Hendro Nurhadi ; b ; hdnurhadi@me.its.ac.id" class="auth_mail" title="E-mail the corresponding author
- 关键词：AUV ; Ensemble Kalman Filter ; Fuzzy Kalman Filter
- 刊名：Expert Systems with Applications
- 出版年：2017
- 出版时间：February 2017
- 年：2017
- 卷：68
- 期：Complete
- 页码：29-35
- 全文大小：644 K
文摘
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Ensemble Kalman Filter (EnKF) algorithm can be applied to estimate AUV position.
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Fuzzy Kalman Filter (FKF) algorithm can be applied to estimate AUV position.
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The system dynamic of AUV motion is used for true trajectory of estimation.
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EnKF estimation is better than FKF estimation in AUV position estimation.
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Performance of each method based on RMSE and computational time.