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

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.

[1]  A. Siegel Robust regression using repeated medians , 1982 .

[2]  J. A. Catipovic,et al.  Design and performance analysis of a Digital Acoustic Telemetry System for the short range underwater channel , 1984 .

[3]  B. Ripley,et al.  Robust Statistics , 2018, Wiley Series in Probability and Statistics.

[4]  Erik G. Ström,et al.  Cooperative Wireless Sensor Network Positioning via Implicit Convex Feasibility , 2013, IEEE Transactions on Signal Processing.

[5]  Guangjie Han,et al.  Localization Algorithms of Underwater Wireless Sensor Networks: A Survey , 2012, Sensors.

[6]  Adam Zielinski,et al.  An eigenpath underwater acoustic communication channel model , 1995, 'Challenges of Our Changing Global Environment'. Conference Proceedings. OCEANS '95 MTS/IEEE.

[7]  Andreas F. Molisch,et al.  Ultra-Wide-Band Propagation Channels , 2009, Proceedings of the IEEE.

[8]  Hwee Pink Tan,et al.  LOS and NLOS Classification for Underwater Acoustic Localization , 2014, IEEE Transactions on Mobile Computing.

[9]  Reza Javidan,et al.  A robust method for underwater wireless sensor joint localization and synchronization , 2017 .

[10]  R. Michael Buehrer,et al.  Handbook of Position Location: Theory, Practice and Advances , 2011 .

[11]  Y. Zakharov,et al.  Channel Modeling for Underwater Acoustic Network Simulation , 2020, IEEE Access.

[12]  Wing-Kin Ma,et al.  Accurate approximation algorithm for TOA-based maximum likelihood mobile location using semidefinite programming , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[13]  João M. F. Xavier,et al.  Simple and Fast Convex Relaxation Method for Cooperative Localization in Sensor Networks Using Range Measurements , 2014, IEEE Transactions on Signal Processing.

[14]  Milica Stojanovic,et al.  Underwater sensor networks: applications, advances and challenges , 2012, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[15]  C. Sidney Burrus,et al.  Iterative reweighted least-squares design of FIR filters , 1994, IEEE Trans. Signal Process..

[16]  Michael B. Porter,et al.  Ray/Beam Tracing for Modeling the Effects of Ocean and Platform Dynamics , 2013, IEEE Journal of Oceanic Engineering.

[17]  Zhi-Quan Luo,et al.  Distributed sensor network localization using SOCP relaxation , 2008, IEEE Transactions on Wireless Communications.

[18]  Andrew Zisserman,et al.  Multiple View Geometry in Computer Vision (2nd ed) , 2003 .

[19]  Andreas F. Molisch,et al.  A Survey on the Impact of Multipath on Wideband Time-of-Arrival Based Localization , 2018, Proceedings of the IEEE.

[20]  P. Rousseeuw Least Median of Squares Regression , 1984 .

[21]  Yahong Rosa Zheng,et al.  Statistical channel modeling of wireless shallow water acoustic communications from experiment data , 2010, 2010 - MILCOM 2010 MILITARY COMMUNICATIONS CONFERENCE.

[22]  Sophie Keller Fundamentals Of Statistical Processing Vol I Estimation Theory , 2016 .

[23]  M. Porter,et al.  Gaussian beam tracing for computing ocean acoustic fields , 1987 .

[24]  M. B. Pursley Direct-sequence spread-spectrum communications for multipath channels , 2002 .

[25]  Jeffrey A. Neasham,et al.  Spread-Spectrum Techniques for Bio-Friendly Underwater Acoustic Communications , 2018, IEEE Access.

[26]  R. Fay Acoustic Communication , 2003, Springer Handbook of Auditory Research.

[27]  Paul Tseng,et al.  Second-Order Cone Programming Relaxation of Sensor Network Localization , 2007, SIAM J. Optim..

[28]  Dario Pompili,et al.  Challenges for efficient communication in underwater acoustic sensor networks , 2004, SIGBED.

[29]  Shengli Zhou,et al.  Prospects and Problems of Wireless Communication for Underwater Sensor , 2008 .

[30]  Milica Stojanovic,et al.  Statistical characterization and capacity of shallow water acoustic channels , 2009, OCEANS 2009-EUROPE.

[31]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[32]  G. Loubet,et al.  Underwater spread-spectrum communications , 1997, Oceans '97. MTS/IEEE Conference Proceedings.

[33]  Milica Stojanovic,et al.  Underwater acoustic communication channels: Propagation models and statistical characterization , 2009, IEEE Communications Magazine.

[34]  Xiuzhen Cheng,et al.  Silent Positioning in Underwater Acoustic Sensor Networks , 2008, IEEE Transactions on Vehicular Technology.

[35]  Yong-Kon Lim,et al.  Underwater acoustic channel characterization at 6kHz and 12kHz in a shallow water near Jeju Island , 2013, 2013 OCEANS - San Diego.

[36]  M. Stojanovic,et al.  Statistical Characterization and Computationally Efficient Modeling of a Class of Underwater Acoustic Communication Channels , 2013, IEEE Journal of Oceanic Engineering.

[37]  Charalampos Tsimenidis,et al.  Robust TDA-MAC for practical underwater sensor network deployment: lessons from USMART sea trials , 2018, WUWNet.

[38]  Yuriy V. Zakharov,et al.  TDA-MAC: TDMA Without Clock Synchronization in Underwater Acoustic Networks , 2018, IEEE Access.

[39]  Hwee-Pink Tan,et al.  NLOS identification using a hybrid ToA-signal strength algorithm for underwater acoustic localization , 2010, OCEANS 2010 MTS/IEEE SEATTLE.

[40]  B. Bingham,et al.  On the Design of Direct Sequence Spread-Spectrum Signaling for Range Estimation , 2007, OCEANS 2007.

[41]  H. T. Mouftah,et al.  Localization techniques for underwater acoustic sensor networks , 2010, IEEE Communications Magazine.

[42]  Mandar Chitre,et al.  A high-frequency warm shallow water acoustic communications channel model and measurements. , 2007, The Journal of the Acoustical Society of America.

[43]  Jiawang Nie,et al.  Sum of squares method for sensor network localization , 2006, Comput. Optim. Appl..

[44]  Desmond P. Taylor,et al.  A Statistical Model for Indoor Multipath Propagation , 2007 .

[45]  M. Stojanovic,et al.  Underwater Acoustic Communications: Design Considerations on the Physical Layer , 2008, 2008 Fifth Annual Conference on Wireless on Demand Network Systems and Services.

[46]  Jun-Hong Cui,et al.  Comparing underwater MAC protocols in real sea experiment , 2013, 2013 IFIP Networking Conference.

[47]  Christophe Laot,et al.  Stochastic Replay of Non-WSSUS Underwater Acoustic Communication Channels Recorded at Sea , 2011, IEEE Transactions on Signal Processing.

[48]  M. Badiey,et al.  Modeling Acoustic Signal Fluctuations Induced by Sea Surface Roughness , 2005 .

[49]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[50]  Zhiqun Daniel Deng,et al.  Contributed Review: Source-localization algorithms and applications using time of arrival and time difference of arrival measurements. , 2016, The Review of scientific instruments.

[51]  Jian Li,et al.  Exact and Approximate Solutions of Source Localization Problems , 2008, IEEE Transactions on Signal Processing.

[52]  W. Jobst,et al.  Coherence estimates for signals propagated through acoustic channels with multiple paths , 1979 .

[53]  Yvan Petillot,et al.  Ocean Monitoring Framework based on Compressive Sensing using Acoustic Sensor Networks , 2018, OCEANS 2018 MTS/IEEE Charleston.

[54]  C. Tindle,et al.  Wavefronts and waveforms in deep-water sound propagation. , 2002, The Journal of the Acoustical Society of America.

[55]  D K Smith,et al.  Numerical Optimization , 2001, J. Oper. Res. Soc..

[56]  Andrew Zisserman,et al.  MLESAC: A New Robust Estimator with Application to Estimating Image Geometry , 2000, Comput. Vis. Image Underst..

[57]  Steffen Beich Alternative Methods Of Regression , 2016 .