Underwater acoustic localization with uncertainties in propagation speed and time synchronization

2016 ◽  
Author(s):  
Chaofeng He ◽  
Yiyin Wang ◽  
Cailian Chen ◽  
Xinping Guan
Keyword(s):  
Time Synchronization ◽  
Propagation Speed ◽  
Underwater Acoustic ◽  
Acoustic Localization

Simultaneous Multi-points Measurement in Underwater Acoustic Localization

2021 ◽  
Author(s):  
Atsushi Wada ◽  
Shingo Yoshizawa ◽  
Satoshi Yuasa ◽  
Hideki Sugimoto
Keyword(s):  
Underwater Acoustic ◽  
Acoustic Localization

scholarly journals Underwater TDOA Acoustical Location Based on Majorization-Minimization Optimization

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4457
Author(s):  
Shuangshuang Li ◽  
Haixin Sun ◽  
Hamada Esmaiel
Keyword(s):  
Information Matrix ◽  
Initial Point ◽  
Auxiliary Function ◽  
Localization Algorithm ◽  
Underwater Acoustic ◽  
Acoustic Localization ◽  
Mm Algorithm ◽  
Localization Scheme ◽  
Localization Algorithms ◽  
Gradient Based

Underwater acoustic localization is a useful technique applied to any military and civilian applications. Among the range-based underwater acoustic localization methods, the time difference of arrival (TDOA) has received much attention because it is easy to implement and relatively less affected by the underwater environment. This paper proposes a TDOA-based localization algorithm for an underwater acoustic sensor network using the maximum-likelihood (ML) ratio criterion. To relax the complexity of the proposed localization complexity, we construct an auxiliary function, and use the majorization-minimization (MM) algorithm to solve it. The proposed localization algorithm proposed in this paper is called a T-MM algorithm. T-MM is applying the MM algorithm to the TDOA acoustic-localization technique. As the MM algorithm iterations are sensitive to the initial points, a gradient-based initial point algorithm is used to set the initial points of the T-MM scheme. The proposed T-MM localization scheme is evaluated based on squared position error bound (SPEB), and through calculation, we get the SPEB expression by the equivalent Fisher information matrix (EFIM). The simulation results show how the proposed T-MM algorithm has better performance and outperforms the state-of-the-art localization algorithms in terms of accuracy and computation complexity even under a high presence of underwater noise.

Underwater acoustic localization of sperm whales with a pair of hydrophones

2018 ◽  
Vol 144 (3) ◽  
pp. 1911-1911
Author(s):  
Emmanuel Skarsoulis ◽  
George Piperakis ◽  
Michael Kalogerakis ◽  
Emmanuel Orfanakis ◽  
Panagiotis Papadakis ◽  
...  
Keyword(s):  
Sperm Whales ◽  
Underwater Acoustic ◽  
Acoustic Localization
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