Localization of an Array of Hydrophones Towed by an Autonomous Underwater Vehicle. Arrichiello, F., Sarkar, S., Chiaverini, S., & Antonelli, G. In MED 2018 - 26th Mediterranean Conference on Control and Automation, 2018. doi abstract bibtex © 2018 IEEE.The paper addresses the localization problem of an array of hydrophones mounted on a flexible streamer towed by an Autonomous Underwater Vehicle (AUV). The considered system has been developed in the framework of the H2020 European project WiMUST and it is finally aimed at performing seismic surveys by acoustic means to explore the sea bottom subsurface. In particular, in the project's scenario, the acoustic seismic survey is performed having two autonomous surface vessels, carrying acoustic sources named sparkers, and a team of AUVs, towing a streamer each. The time of flight with which the waves generated from the sparkers reflect in the sea sub-bottom layers and return to the hydrophones provides valuable information about the properties of the ocean subsurface. However, for a proper processing of the acoustic data, there is the need to estimate the hydrophones' positioning. Here, we present a localization strategy for the described system based on an Extended Kalman Filter (EKF) that uses the dynamic model of the AUV-streamer system and the range measurements from sparkers to hydrophones as extracted from the seismic acoustic signals. The proposed approach has been tested in numerical case studies built using data extracted from the experimental tests performed in the framework of the WiMUST project.
@inproceedings{Arrichiello2018,
author = {Arrichiello, Filippo and Sarkar, Soumic and Chiaverini, Stefano and Antonelli, Gianluca},
title = {Localization of an Array of Hydrophones Towed by an Autonomous Underwater Vehicle},
booktitle = {MED 2018 - 26th Mediterranean Conference on Control and Automation},
doi = {10.1109/MED.2018.8443013},
abstract = {© 2018 IEEE.The paper addresses the localization problem of an array of hydrophones mounted on a flexible streamer towed by an Autonomous Underwater Vehicle (AUV). The considered system has been developed in the framework of the H2020 European project WiMUST and it is finally aimed at performing seismic surveys by acoustic means to explore the sea bottom subsurface. In particular, in the project's scenario, the acoustic seismic survey is performed having two autonomous surface vessels, carrying acoustic sources named sparkers, and a team of AUVs, towing a streamer each. The time of flight with which the waves generated from the sparkers reflect in the sea sub-bottom layers and return to the hydrophones provides valuable information about the properties of the ocean subsurface. However, for a proper processing of the acoustic data, there is the need to estimate the hydrophones' positioning. Here, we present a localization strategy for the described system based on an Extended Kalman Filter (EKF) that uses the dynamic model of the AUV-streamer system and the range measurements from sparkers to hydrophones as extracted from the seismic acoustic signals. The proposed approach has been tested in numerical case studies built using data extracted from the experimental tests performed in the framework of the WiMUST project.},
year = {2018},
}
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The considered system has been developed in the framework of the H2020 European project WiMUST and it is finally aimed at performing seismic surveys by acoustic means to explore the sea bottom subsurface. In particular, in the project's scenario, the acoustic seismic survey is performed having two autonomous surface vessels, carrying acoustic sources named sparkers, and a team of AUVs, towing a streamer each. The time of flight with which the waves generated from the sparkers reflect in the sea sub-bottom layers and return to the hydrophones provides valuable information about the properties of the ocean subsurface. However, for a proper processing of the acoustic data, there is the need to estimate the hydrophones' positioning. Here, we present a localization strategy for the described system based on an Extended Kalman Filter (EKF) that uses the dynamic model of the AUV-streamer system and the range measurements from sparkers to hydrophones as extracted from the seismic acoustic signals. The proposed approach has been tested in numerical case studies built using data extracted from the experimental tests performed in the framework of the WiMUST project.","year":"2018","bibtex":"@inproceedings{Arrichiello2018,\n author = {Arrichiello, Filippo and Sarkar, Soumic and Chiaverini, Stefano and Antonelli, Gianluca},\n title = {Localization of an Array of Hydrophones Towed by an Autonomous Underwater Vehicle},\n booktitle = {MED 2018 - 26th Mediterranean Conference on Control and Automation},\n doi = {10.1109/MED.2018.8443013},\n abstract = {© 2018 IEEE.The paper addresses the localization problem of an array of hydrophones mounted on a flexible streamer towed by an Autonomous Underwater Vehicle (AUV). The considered system has been developed in the framework of the H2020 European project WiMUST and it is finally aimed at performing seismic surveys by acoustic means to explore the sea bottom subsurface. In particular, in the project's scenario, the acoustic seismic survey is performed having two autonomous surface vessels, carrying acoustic sources named sparkers, and a team of AUVs, towing a streamer each. The time of flight with which the waves generated from the sparkers reflect in the sea sub-bottom layers and return to the hydrophones provides valuable information about the properties of the ocean subsurface. However, for a proper processing of the acoustic data, there is the need to estimate the hydrophones' positioning. 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