Underwater Locator Beacon signal propagation on tropical waters

Rafael, Barmak; Oliveira, Andre L. S. C. de; Thiago, Pedro Sao; Santos, Francisco dos; Lopes, Marco V. R.; Cernicchiaro, G.

doi:10.1109/rioacoustics.2017.8349738

Cited by 4 publications

(4 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As can be seen from Figure 8, the described system allows not only to monitor the location of the object being searched for but also to correct the vessel's heading, determine the depth of the object being searched, as well as the water temperature using its built-in sensor. The RER and BRE fields correspond to the current and best values of the residual function (2). According to the calculated positions of the object, the deviation from the real position obtained using GNSS just before the submersion is in the range of 2-2.5 meters in both experiments, which is comparable with the accuracy of the used GNSS modules [22].…”

Section: Fig 8 -Screenshot Of the Main Application Windowmentioning

confidence: 82%

“…), lack of accuracy provided by USBL systems or any weight and size restrictions associated with the applied vessel. Also, in some cases, the deployment of a long baseline (especially a bottom one) is completely unjustified, for example, when quite rare (or single) measurements of the underwater object's position are required, or in case of a search (for example, accidentally submerged objectsships or aircraft [1] [2]) in a fairly wide area, where it is impossible to install a long baseline system of the required dimensions. Particularly noteworthy is the positioning of the nodes of Underwater wireless network of autonomous sensors UWSN [3] [4] which often require only a rare or even a one-time estimation of their location.…”

Section: Introductionmentioning

confidence: 99%

“…xrn, yrn and drn -the coordinates of the nearest base point and the projection of the slant range to it, respectively. Having performed a complete search over β in the range from 0 to 2π with a certain step (in this work, a search with a step of 10 degrees and then a search with a step of 1 degree in the range of +/-10 degrees from the previous minimum position are used), one can obtain an approximate position of the global minimum of the function (2), which then will be used as the initial one for solving a two-dimensional problem. Figure 3 shows a comparison of the effectiveness (number of iterations) of solving the problem of estimating the location of the desired object of random data with and without the application of preliminary one-dimensional optimization.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Position Estimation of Autonomous Underwater Sensors Using the Virtual Long Baseline Method

Dikarev¹,

Dmitriev²,

Kubkin³

et al. 2019

IJWMN

View full text Add to dashboard Cite

This article contains a description of a mathematical model of an acoustic system for positioning autonomous underwater sensors using the virtual long base method, which can be used during the vessel's collection of information over the deployed underwater network of autonomous sensors (underwater wireless sensors network), during the initial determination of the geographical position of the bottom long baseline elements or search, including cooperative, with the use of a swarm of autonomous surface vehicles (UASV) of emergency submerged objects equipped with an emergency beacon (for example, aircraft and ships); The article provides a scheme of an experimental set of equipment, as well as a description of the conducted field experiments and their results.

show abstract

Section: Fig 8 -Screenshot Of the Main Application Windowmentioning

confidence: 82%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Position Estimation of Autonomous Underwater Sensors Using the Virtual Long Baseline Method

Dikarev¹,

Dmitriev²,

Kubkin³

et al. 2019

IJWMN

View full text Add to dashboard Cite

show abstract

“…This is the unit for acoustic transmission power, which means that the ULB sends pings with a power of 160.5 dB relative to one micropascal (reference pressure underwater). The signal's pulse length is 10 ms and the pulse interval is 1 s. [3] There exist novel technologies that eject a flight recorder before impact. [21] The recorder is designed to float and can communicate with satellites to update on the position of the flight recorder.…”

Section: Background and Related Work 21 Flight Recorder Technologymentioning

confidence: 99%

Underwater Acoustic Location Estimation of Flight Recorder Using Onboard Ad Hoc Wireless Sensor Network

Wiepking,

Greef,

Ozcelebi

2022

2022 IEEE Ocean Engineering Technology and Innovation Conference: Management and Conservation for Sustainable and Resilient Mar

View full text Add to dashboard Cite

Underwater Wireless Sensor Networks (UWSN) are an upcoming technology for various underwater applications, such as environment monitoring and localization of objects. An important use case for underwater object localization is locating the underwater locator beacon (ULB) of a flight recorder, commonly known as a 'black box', after the unfortunate event of an oceanic flight crash. Current technology for finding this black box uses hydrophone-equipped vessels or autonomous underwater vehicles (AUV). To increase the probability of finding the black box using these technologies, a well-estimated position of the flight crash is required which is not always available after oceanic crashes. Also, these technologies need to travel to the crash location which takes time and complicates the search process. To circumvent these problems, this study presents an alternative approach to locating the sinking black box using an UWSN onboard of the aircraft that starts deploying in the ocean after the detection of an oceanic crash event. By registering acoustic ping signals of the ULB, the nodes in the network collaboratively estimate the source location using a Time-Difference of Arrival (TDoA) approach. Underwater nodes are used to extend network coverage to deep-ocean levels and communicate their findings by utilizing wireless acoustic modems. Use of the underwater acoustic medium imposes various challenges such as a slow propagation speed that changes over depth, limited bandwidth and multipath propagation. In this study a set of strategies is introduced to be incorporated in a UWSN that collectively enables localization of the ULB while taking into account the complexities imposed by the underwater acoustic medium. Also a set of communication and scheduling protocols are included that tailor the network hierarchy. To assess the performance of onboard UWSN-based black box localization, a custom Underwater Acoustic Localization Simulator (UWALSim) is built that utilizes BELLHOP for realistic underwater sound propagation modelling. Furthermore, the simulator can detect signal collisions, simulate noise on the acoustic channel and models energy consumption of nodes in the network. Several crash scenarios and variations in self-positioning performance have been used to assess the performance of this approach on localizing the black box. These results show that proper self-positioning is crucial to successfully locate the black box. Also partial deployment of the network in the ocean before the wreckage with the black box starts sinking is highly preferable. When satisfying the requirements in self-positioning performance and partial network deployment, the network is able to locate the black box with an error less than 50 meters for at least 75% of the transmitted ULB pings on a 10-second ping interval. Depending on the scenario, experimental results show that this approach provides accurate black box location estimations after 5-25 minutes since the wreckage with the black box started sinking. Therefore, an onboard ad-hoc UWSN he...

show abstract

LocoMote: AI-Driven Sensor Tags for Fine-Grained Undersea Localization and Sensing

Saha,

Davis,

Sandha

et al. 2024

IEEE Sensors J.

View full text Add to dashboard Cite

Underwater Locator Beacon signal propagation on tropical waters

Cited by 4 publications

References 3 publications

Position Estimation of Autonomous Underwater Sensors Using the Virtual Long Baseline Method

Position Estimation of Autonomous Underwater Sensors Using the Virtual Long Baseline Method

Underwater Acoustic Location Estimation of Flight Recorder Using Onboard Ad Hoc Wireless Sensor Network

LocoMote: AI-Driven Sensor Tags for Fine-Grained Undersea Localization and Sensing

Contact Info

Product

Resources

About