Design and Performance Analysis of Underwater Acoustic Sensor Networks

<p>The greatest challenge in underwater acoustic communication systems is the minimization of underwater impact noise. This article offers an empirical example for determining the statistical properties of underwater acoustic noise in the in Lake Hamrin. The data are measured from various depths reached in Lake Hamrin, Diyala, Iraq. In most communication systems, noise is assumed to be additive as well as Gaussian. Underwater acoustic noise (UWAN) isn't only thermal noise, it also includes other components to the UWAN: turbulence, wind and shipping noises. Thus, it should be assumed that the acoustic noise is colored noise instead of white noise. Intermittent noise in the oceans and seas frequently includes significant Non-Gaussian elements. The samples noise data are analyzed in actual time for various depths of 1 meter, 3 meter and 5 meter in order to limit the statistical properties of underwater acoustic noise in Lake Hamrin, Diyala, Iraq such as the autocorrelation function (ACF), the probability density function (PDF) and also power spectral density (PSD). The experimental results showed that the noise of the Tigris river is a color noise and does not follow the Gaussian distribution.</p>

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“…The total power spectral density is the sum of thermal, wind, ship and turbulence and may be calculated using (5) [24], [28].…”

Section: Underwater Acoustic Noisementioning

confidence: 99%

Statistical properties of underwater acoustic noise in Lake Hamrin, Diyala, Iraq

Murad

Al‐Aboosi

2022

IJEECS

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“…The acoustic waves used in the communication medium are known to limit the performance of the UWASN in terms of its bandwidth and latency. This issue is mainly due to its high path loss and end-to-end delay (Ghaleb et al, 2017). Due to the hostile underwater environment, it is very challenging to develop effective and efficient tracking and localization algorithms for the autonomous underwater vehicles (AUVs).…”

Section: Introductionmentioning

confidence: 99%

Measurement and compensation of spillover effect in underwater acoustic sensor networks during target localization

Reddy

Prateek

Arya

2022

Transactions of the Institute of Measurement and Control

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Localization in underwater acoustic sensor networks (UWASNs) depends critically on the mobility pattern of the topology as well as the target node. Prior literature has attempted to localize static as well as dynamic sensors. However, unintentional movement of the sensor network introduces localization errors which add up cumulatively and disrupt the normal functioning of an underwater sensor network. In the present work, the concept of spillover has been defined to denote these unintentional movements. The genesis of spillover has been discussed with respect to the signal model. A theorem is proposed to describe the consequence of spillover on the UWASN. The problem of spillover is quantified mathematically. The loss of localization performance due to the spillover effect is then measured with the formulation of a control function which incorporates delay time. To mitigate the losses, a spillover compensation (SoC) algorithm is proposed. SoC utilizes a discretization technique to reduce the variance of sensor position and to enhance localization accuracy. It improves the performance of localization by at least 23.15% and reduces the localization error by 31% up to 600 m. Through a series of computations using parameters such as root mean square (RMS) positioning error and RMS velocity error, the theoretical findings are verified and compared with standard techniques. Diversity in deployment scenarios is taken care of using variance and sensor speed. The proposed technique shall be useful to create spillover-aware systems in underwater cybernetic localization and UWASNs in general.

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Design and Performance Analysis of Underwater Acoustic Sensor Networks

Cited by 2 publications

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Statistical properties of underwater acoustic noise in Lake Hamrin, Diyala, Iraq

Statistical properties of underwater acoustic noise in Lake Hamrin, Diyala, Iraq

Measurement and compensation of spillover effect in underwater acoustic sensor networks during target localization

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