Minimizing position uncertainty for under-ice autonomous underwater vehicles

Chen, Baozhi; Pompili, Dario

doi:10.1016/j.comnet.2013.09.009

Cited by 5 publications

(4 citation statements)

References 21 publications

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“…UAS design is being progressively improved. At this proposal a better underwater localisation of these vehicles, which is difficult to be achieved especially under ice surfaces owing to the lower global positioning system (GPS) signal, represents the purpose of a study that has been recently led by Chen and Pompili (2013).…”

Section: State Of Art Within Marine Domainmentioning

confidence: 99%

Simulation of autonomous systems in the extended marine domain

Tremori

Agresta²,

Ferrando³

2016

IJSPM

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This paper is focused on characteristics and goals of an integrated architecture which aims at reproducing joint interoperability among autonomous systems. The paper proposes an experimentation over a scenario developed for the maritime context that uses an innovative simulator. The authors' goal, during such research, consists of identifying requirements related to these simulators so that they accurately keep into account the most important elements affecting real operative context. This analysis is addressing training (Kennedy, 2010), engineering and it could be further developed for supporting or operation supervision. General architecture devoted to integrate such simulators within a federation, together with the approach that has been used in order to carry out this operation, represent the subjects of this paper; the mission environment has been created with the only goal to test the federation, and similarly simulation architecture and conceptual models are validated through proposed preliminary activities

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Section: State Of Art Within Marine Domainmentioning

confidence: 99%

Simulation of autonomous systems in the extended marine domain

Tremori

Agresta²,

Ferrando³

2016

IJSPM

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“…To ensure safe navigation, accurate object localization, especially for the threatening aerial object, is one of the primary challenges for AUVs nowadays [4]. There have been some important technologies applied for AUV object localization, such as GPS [5], radar, laser [6], and multibeam acoustic [7]. However, all of the technologies mentioned previously are of limited value in applications as invisibility of AUVs is often compromised.…”

Section: Introductionmentioning

confidence: 99%

Accurate Aerial Object Localization Using Gravity and Gravity Gradient Anomaly

Zhou

Tian

2015

IEEE Geosci. Remote Sensing Lett.

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Autonomous underwater vehicles (AUVs) have been widely used in diverse contexts, especially military affairs. The smooth operation of the AUV requires accurate localization of surrounding objects, especially the aerial objects. In this letter, a novel and practical method is presented for aerial object localization by using gravity and gravity gradient anomaly. Different from the state-of-the-art methods, such as GPS, radar, and laser, the proposed method runs in a passive manner and achieves AUV invisibility without energy emission. Compared with the object localization methods based on gravity and gravity gradient inversion, the proposed method is more practical as no large area gravity and gravity gradient measurements are needed to estimate the object mass. Experimental results demonstrate that the proposed method performs better than the existing methods.

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“…Section (3) describes the proposed MANCL localization algorithm in detail. Section (4) gives a detailed analysis of simulation results. And finally, Section (5) makes a conclusion and discusses future research issues of localization algorithms in UASNs.…”

Section: Introductionmentioning

confidence: 99%

“…For these applications, localization is a fundamental issue. Localization in UASNs is challenging due to several reasons: (I) unavailability of a global positioning system (GPS) ; (II) high and variable propagation delays because the communication links are based on acoustic wireless technology ; (III) limited bandwidth capacity and energy; and (IV) difficult to deploy sensor nodes at precise locations in underwater environments . Considering these challenges, it is necessary to develop a localization algorithm to reduce distance measurement error and improve localization accuracy and localization ratio, even in sparse underwater sensor networks.…”

Section: Introductionmentioning

confidence: 99%

MANCL: a multi‐anchor nodes collaborative localization algorithm for underwater acoustic sensor networks

Han

Zhang

Liu

et al. 2014

Wireless Communications

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Localization is an essential and major issue for underwater acoustic sensor networks (UASNs). Almost all the applications in UASNs are closely related to the locations of sensors. In this paper, we propose a multi‐anchor nodes collaborative localization (MANCL) algorithm, a three‐dimensional (3D) localization scheme using anchor nodes and upgrade anchor nodes within two hops for UASNs. The MANCL algorithm divides the whole localization process into four sub‐processes: unknown node localization process, iterative location estimation process, improved 3D Euclidean distance estimation process, and 3D DV‐hop distance estimation process based on two‐hop anchor nodes. In the third sub‐process, we propose a communication mechanism and a vote mechanism to determine the temporary coordinates of unknown nodes. In the fourth sub‐process, we use two‐hop anchor nodes to help localize unknown nodes. We also evaluate and compare the proposed algorithm with a large‐scale localization algorithm through simulations. Results show that the proposed MANCL algorithm can perform better with regard to localization ratio, average localization error, and energy consumption in UASNs. Copyright © 2014 John Wiley & Sons, Ltd.

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Minimizing position uncertainty for under-ice autonomous underwater vehicles

Cited by 5 publications

References 21 publications

Simulation of autonomous systems in the extended marine domain

Simulation of autonomous systems in the extended marine domain

Accurate Aerial Object Localization Using Gravity and Gravity Gradient Anomaly

MANCL: a multi‐anchor nodes collaborative localization algorithm for underwater acoustic sensor networks

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