Surface Based Underwater Communications

In an underwater environment signal propagation for the acoustic channel is subject to major multipath effect. Therefore, most underwater communication schemes require that the position of the transmitter or receiver is fixed while using directional antennas in order to ensure high signal-to-noise ratio. However, such a requirement hinders node discovery and ad-hoc formation of underwater networks and restraints communication between autonomous underwater vehicles (AUVs) where node locations change over time. This paper proposes a novel approach to underwater communications by relying on the water surface to establish communication links. The proposed surface-based reflection (SBR) model works by requiring the transmitting node to direct its energy towards the water surface. The receiver then applies homomorphic deconvolution techniques to determine the channels impulse response used in obtaining the reflected signal. The receiver is then able to determine the location of the transmitter by triangulating the transmitted and reflected signals with respect to the water surface. Simulation experiments are provided to validate the SBR approach.

[1]  R. Weber,et al.  Performance enhancement of blind adaptive equalizers using environmental knowledge , 2003, Oceans 2003. Celebrating the Past ... Teaming Toward the Future (IEEE Cat. No.03CH37492).

[2]  John Heidemann,et al.  Understanding and exploiting the acoustic propagation delay in underwater sensor networks , 2009 .

[3]  A. W. M. van den Enden,et al.  Discrete Time Signal Processing , 1989 .

[4]  Michael B. Porter,et al.  Computational Ocean Acoustics , 1994 .

[5]  A. Quinquis,et al.  Denoising underwater signals propagating through multi-path channels , 2005, Europe Oceans 2005.

[6]  Bayan S. Sharif,et al.  A blind multichannel combiner for long range underwater communications , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[7]  H. Hashemi,et al.  The indoor radio propagation channel , 1993, Proc. IEEE.

[8]  Dario Pompili,et al.  Underwater acoustic sensor networks: research challenges , 2005, Ad Hoc Networks.

[9]  A. Quazi,et al.  Underwater acoustic communications , 1982, IEEE Communications Magazine.

[10]  I.J.G. Scott,et al.  Acoustic wave propagation in underwater shallow channel environments , 2007, OCEANS 2007 - Europe.

[11]  M. B. Porter Acoustic models and sonar systems , 1993 .

[12]  B.M. Howe,et al.  Sensor networks for cabled ocean observatories , 2004, Proceedings of the 2004 International Symposium on Underwater Technology (IEEE Cat. No.04EX869).

[13]  J.E. Faugstadmo,et al.  HAIN: an integrated acoustic positioning and inertial navigation , 2004, Oceans '04 MTS/IEEE Techno-Ocean '04 (IEEE Cat. No.04CH37600).

[14]  Juan Carlos,et al.  Review of "Discrete-Time Speech Signal Processing - Principles and Practice", by Thomas Quatieri, Prentice-Hall, 2001 , 2003 .

[15]  G. Loubet,et al.  Underwater acoustic channel simulations for communication , 1994, Proceedings of OCEANS'94.

[16]  Thomas Quatieri,et al.  Discrete-Time Speech Signal Processing: Principles and Practice , 2001 .

[17]  Paul C. Etter,et al.  Underwater acoustic modeling : principles, techniques and applications , 1996 .

[18]  P. C. Etter Underwater Acoustic Modeling: Principles, techniques and applications, Second Edition , 1995 .

[19]  G. Carter Coherence and time delay estimation , 1987, Proceedings of the IEEE.