Time reversal communication using vertical particle velocity and pressure signals in shallow water

Kim, Sunhyo; Kim, Hyeonsu; Jung, Seom‐Kyu; Choi, Jee Woong

doi:10.1016/j.adhoc.2019.03.008

Cited by 5 publications

(9 citation statements)

References 23 publications

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“…In contrast, a vector sensor has good spatial efficiency because it measures the three directional vector quantities as well as the pressure change at a single point. Accordingly, it can be used as a SIMO system, as shown in Figure 1b [22,23,24].…”

Section: Communication Performance Based On Single-vector Sensorsmentioning

confidence: 99%

“…The BER performance is finally evaluated. See [24] for a detailed description of vector sensor communication using particle velocity and pressure signals.…”

Section: Communication Performance Based On Single-vector Sensorsmentioning

confidence: 99%

“…The pressure gradient can be approximately estimated using two pressure signals received at two pressure sensors placed close together. The particle velocity is given by [24]:v(t)= 1ρ0 ∫0tP2(τ)− P1(τ)ddτ where P1 and P2 are the acoustic pressure signals at the two adjacent sensors, d is the sensor spacing between two sensors, ρ0 is the water density, and τ is the time variable. The acoustic pressure is equivalent to the particle velocity in a particular direction multiplied by the acoustic impedance, which is ρ0c, where c is water sound speed.…”

Section: Communication Performance Based On Single-vector Sensorsmentioning

confidence: 99%

“…In recent years, the propagation properties of acoustic vector quantities such as acceleration or acoustic particle velocity have been studied [17,18,19]. Vector sensors have been applied in several areas, including target detection and tracking, noise reduction, and acoustic communication [20,21,22,23,24]. A vector sensor measures the three directional components of the vector quantities, and accordingly, a diversity gain can be achieved even when a single-vector sensor is used.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, a vector sensor measuring the particle velocity is used as a sensor node of a UWASN, with the aim of improving the communication performance and the spatial efficiency. The outputs of the vector sensor are considered to be the outputs of a single-input multiple-output (SIMO) communication system [22,23,24]. The optimal algorithm proposed in our previous paper [13] is then applied to obtain the optimal deployment scheme for the single-vector sensor nodes.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Deployment of Vector Sensor Nodes in Underwater Acoustic Sensor Networks

Kim

Choi

2019

Sensors

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Underwater acoustic sensor networks have recently attracted considerable attention as demands on the Internet of Underwater Things (IoUT) increase. In terms of efficiency, it is important to achieve the maximum communication coverage using a limited number of sensor nodes while maintaining communication connectivity. In 2017, Kim and Choi proposed a new deployment algorithm using the communication performance surface, which is a geospatial information map representing the underwater acoustic communication performance of a targeted underwater area. In that work, each sensor node was a vertically separated hydrophone array, which measures acoustic pressure (a scalar quantity). Although an array receiver is an effective system to eliminate inter-symbol interference caused by multipath channel impulse responses in underwater communication environments, a large-scale receiver system degrades the spatial efficiency. In this paper, single-vector sensors measuring the particle velocity are used as underwater sensor nodes. A single-vector sensor can be considered to be a single-input multiple-output communication system because it measures the three directional components of particle velocity. Our simulation results show that the optimal deployment obtained using single-vector sensor nodes is more effective than that obtained using a hydrophone (three-channel vertical-pressure sensor) array.

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Section: Communication Performance Based On Single-vector Sensorsmentioning

confidence: 99%

“…The BER performance is finally evaluated. See [24] for a detailed description of vector sensor communication using particle velocity and pressure signals.…”

Section: Communication Performance Based On Single-vector Sensorsmentioning

confidence: 99%

Section: Communication Performance Based On Single-vector Sensorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimal Deployment of Vector Sensor Nodes in Underwater Acoustic Sensor Networks

Kim

Choi

2019

Sensors

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Effects of Geophony and Anthrophony on the Underwater Acoustic Environment in the East Siberian Sea, Arctic Ocean

Han

Joo²,

Son

et al. 2021

Geophysical Research Letters

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As Arctic warming accelerates, the underwater acoustic environment in the Arctic Ocean is rapidly changing. We present the first results of passive acoustic monitoring in the marginal ice zone of the East Siberian Sea (ESS). A high sea ice concentration (SIC) and seasonal variations in ice cover make the ESS an ideal region to verify how ambient sound levels respond to natural physical processes and anthropogenic activities during summer. Our observations show that the sound level in the ESS exhibits a strong negative correlation with SIC, and the sound level in September, which was higher than that in other months, was 16 dB higher than the annual average. This increase resulted from geophony and anthrophony with the reduction in the SIC, and sound level increased by 13 dB without anthrophony. Our results indicate that ambient sound level in the Arctic Ocean may increase as climate change accelerates sea ice melting.

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Multiple Diversity Using Acoustic Vector Receiver for Shallow-Water Acoustic Communication

Choi,

Kim

et al. 2024

2024 Fifteenth International Conference on Ubiquitous and Future Networks (ICUFN)

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Time reversal communication using vertical particle velocity and pressure signals in shallow water

Cited by 5 publications

References 23 publications

Optimal Deployment of Vector Sensor Nodes in Underwater Acoustic Sensor Networks

Optimal Deployment of Vector Sensor Nodes in Underwater Acoustic Sensor Networks

Effects of Geophony and Anthrophony on the Underwater Acoustic Environment in the East Siberian Sea, Arctic Ocean

Multiple Diversity Using Acoustic Vector Receiver for Shallow-Water Acoustic Communication

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