Underwater Acoustic Noise Model for Shallow Water Communications

2012 ◽  
Author(s):  
José Panaro ◽  
Fábio Lopes ◽  
Leonardo Barreira ◽  
Fidel Souza
Keyword(s):  
Shallow Water ◽  
Acoustic Noise ◽  
Noise Model ◽  
Underwater Acoustic

scholarly journals Diurnal Variability Of Underwater Acoustic Noise Characteristics in Shallow Water

2017 ◽  
Vol 15 (1) ◽  
pp. 314 ◽  
Author(s):  
Yasin Yousif Al-Aboosi ◽  
Abdulrahman Kanaa ◽  
Ahmad Zuri Sha'ameri ◽  
Hussein A. Abdualnabi
Keyword(s):  
Shallow Water ◽  
Acoustic Noise ◽  
Diurnal Variability ◽  
Underwater Acoustic ◽  
Noise Characteristics

scholarly journals Robust Silent Localization of Underwater Acoustic Sensor Network Using Mobile Anchor(s)

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 727
Author(s):  
Rahul Mourya ◽  
Mauro Dragone ◽  
Yvan Petillot
Keyword(s):  
Channel Model ◽  
Low Cost ◽  
Sensor Nodes ◽  
Noise Model ◽  
Robust Estimator ◽  
Acoustic Sensor ◽  
Underwater Acoustic ◽  
Acoustic Channel ◽  
Localization Scheme ◽  
Mobile Anchor

Underwater acoustic sensor networks (UWASNs) can revolutionize the subsea domain by enabling low-cost monitoring of subsea assets and the marine environment. Accurate localization of the UWASNs is essential for these applications. In general, range-based localization techniques are preferred for their high accuracy in estimated locations. However, they can be severely affected by variable sound speed, multipath spreading, and other effects of the acoustic channel. In addition, an inefficient localization scheme can consume a significant amount of energy, reducing the effective life of the battery-powered sensor nodes. In this paper, we propose robust, efficient, and practically implementable localization schemes for static UWASNs. The proposed schemes are based on the Time-Difference-of-Arrival (TDoA) measurements and the nodes are localized passively, i.e., by just listening to beacon signals from multiple anchors, thus saving both the channel bandwidth and energy. The robustness in location estimates is achieved by considering an appropriate statistical noise model based on a plausible acoustic channel model and certain practical assumptions. To overcome the practical challenges of deploying and maintaining multiple permanent anchors for TDoA measurements, we propose practical schemes of using a single or multiple surface vehicles as virtual anchors. The robustness of localization is evaluated by simulations under realistic settings. By combining a mobile anchor(s) scheme with a robust estimator, this paper presents a complete package of efficient, robust, and practically usable localization schemes for low-cost UWASNs.

Experimental Multipath Delay Profile of Underwater Acoustic Communication Channel in Shallow Water

2016 ◽  
Vol 2 (2) ◽  
pp. 351 ◽  
Author(s):  
Yasin Yousif Al_Aboosi ◽  
Ahmad Zuri Sha'ameri
Keyword(s):  
Shallow Water ◽  
Acoustic Communication ◽  
Multipath Propagation ◽  
Water Channel ◽  
Underwater Acoustic Communication ◽  
Communication Performance ◽  
Underwater Acoustic ◽  
Research Fields ◽  
Different Depths ◽  
Major Factors

<p>The shallow water channel is an environment that is of particular interest to many research fields. An underwater acoustic channel is characterized as a multipath channel. Time-varying multipath propagation is one of the major factors that limit the acoustic communication performance in shallow water. This study conducts two underwater acoustic experiments in Tanjung Balau, Johor, Malaysia. A transducer and a hydrophone are submerged at different depths and separated by different distances. Linear frequency modulated (LFM) pulses are chosen as the main transmit signal for the experiments. The cross-correlation between the transmitted and received signals represents the impulse response of the channel (multipath profile). The results show that the amplitude of the successive paths will not rapidly decline, and vice versa, when the distance between the sender and the receiver increases. Moreover, the time difference between the different paths will be small in the case of distance increase. In other words, the successive paths will converge in time.</p>

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