To address the issue of increasing navigation errors in low-cost autonomous underwater vehicles (AUVs) operating without assisted positioning underwater, this paper proposes a Virtual GPS Model (VGPSM) based on deep sequence learning. This model is integrated with an Extended Kalman Filter (EKF) to provide a high-precision navigation solution for AUVs. The VGPSM leverages the time-series characteristics of data from sensors such as the Attitude and Heading Reference System (AHRS) and the Doppler Velocity Log (DVL) while the AUV is on the surface. It learns the relationship between these sensor data and GPS data by utilizing a hybrid model of Long Short-Term Memory (LSTM) and Bidirectional Long Short-Term Memory (Bi-LSTM), which are well-suited for processing and predicting time-series data. This approach constructs a virtual GPS model that generates virtual GPS displacements updated at the same frequency as the real GPS data. When the AUV navigates underwater, the virtual GPS displacements generated using the VGPSM in real-time are used as measurements to assist the EKF in state estimation, thereby enhancing the accuracy and robustness of underwater navigation. The effectiveness of the proposed method is validated through a series of experiments under various conditions. The experimental results demonstrate that the proposed method significantly reduces cumulative errors, with navigation accuracy improvements ranging from 29.2% to 69.56% compared to the standard EKF, indicating strong adaptability and robustness.
机构:
Univ Florence, Dept Ind Engn, Via Santa Marta 3, I-50139 Florence, Italy
Interuniv Ctr Integrated Syst Marine Environm ISM, Rome, ItalyUniv Florence, Dept Ind Engn, Via Santa Marta 3, I-50139 Florence, Italy
Franchi, Matteo
Ridolfi, Alessandro
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Univ Florence, Dept Ind Engn, Via Santa Marta 3, I-50139 Florence, Italy
Interuniv Ctr Integrated Syst Marine Environm ISM, Rome, ItalyUniv Florence, Dept Ind Engn, Via Santa Marta 3, I-50139 Florence, Italy
机构:
Wuhan Univ, GNSS Res Ctr, Wuhan 430072, Peoples R China
Hubei Luojia Lab, Wuhan, Peoples R China
Wuhan Univ, Artificial Intelligence Inst, Wuhan, Peoples R ChinaWuhan Univ, GNSS Res Ctr, Wuhan 430072, Peoples R China
Guo, Chi
Hu, Jianlang
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Wuhan Univ, GNSS Res Ctr, Wuhan 430072, Peoples R ChinaWuhan Univ, GNSS Res Ctr, Wuhan 430072, Peoples R China
Hu, Jianlang
Luo, Yarong
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Wuhan Univ, GNSS Res Ctr, Wuhan 430072, Peoples R ChinaWuhan Univ, GNSS Res Ctr, Wuhan 430072, Peoples R China
机构:
Sun Yat Sen Univ, Nanfang Coll, Guangzhou 510970, Guangdong, Peoples R ChinaSun Yat Sen Univ, Nanfang Coll, Guangzhou 510970, Guangdong, Peoples R China
Zhong, Xiaoying
Tian, Xuejiao
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机构:
Beijing Union Univ, Sch Appl Sci & Technol, Beijing 100101, Peoples R ChinaSun Yat Sen Univ, Nanfang Coll, Guangzhou 510970, Guangdong, Peoples R China
Tian, Xuejiao
Thilak, K. Deepa
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机构:
SRM Inst Sci & Technol, Dept Comp Sci, Kattankulathur, IndiaSun Yat Sen Univ, Nanfang Coll, Guangzhou 510970, Guangdong, Peoples R China
Thilak, K. Deepa
Anbarasan, M.
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Sairam Inst Technol, Chennai, Tamil Nadu, IndiaSun Yat Sen Univ, Nanfang Coll, Guangzhou 510970, Guangdong, Peoples R China