Optimal Deployment of Vector Sensor Nodes in Underwater Acoustic Sensor Networks

Abstract

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.

Passive Source Localization Using Acoustic Intensity in Multipath-Dominant Shallow-Water Waveguide

“…Since POEMS is the vertical line array, only the vertical component of the particle velocity was estimated. The mean acoustic pressure of the two hydrophones can be assumed as the acoustic pressure at the midpoint between two hydrophones [ 18 , 19 , 20 , 21 , 22 , 23 ], which is given by …”

“…As vector quantities have direction as well as magnitude, a vector sensor has the capability to accurately estimate the azimuth and elevation angles of a submerged source while avoiding left–right ambiguity, which is a problem of the line array receiver consisting of hydrophones. Thus, vector sensors have been applied in several areas, including underwater target tracking, acoustic noise reduction, and underwater communication [ 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 ].…”

“…Acoustic particle velocity can be calculated by Euler’s equation with respect to time [ 18 , 19 , 20 , 21 , 22 , 23 ]. If two pressure sensors are close together, the pressure gradient along the axis of two pressure sensors can be approximated through finite difference approximation.…”

Sea lion optimization algorithm based node deployment strategy in underwater acoustic sensor network

“…Sunhyoand Choi 16 proposed an optimal deployment of vector SNs in UASN. The optimal location SN was discovered with the help of hybrid Virtual Force Particle Search Optimization (VFPSO) algorithm which was the combination of Particle Swarm Optimization (PSO) and Virtual Force Algorithm (VFA) algorithms.…”

Design of Shrewd Underwater Routing Synergy Using Porous Energy Shells

“…On the basis of location information of sensor nodes, OR creates an imaginary virtual three-dimensional (3D) pipe from the relay to the sink node to avoid the issue of forwarder set selection (FSR). An energy harvesting-based routing scheme (ARCUN) [13], has been suggested with fixed ratio combining technique (FRC) to strengthen the smart use of energy utilization with controlled data packet load without putting in the medium access control. From the results, it seems that this technique puts extra data forwarding load on the relay nodes which shortens the network lifespan such situation.…”