Characterization of the acoustic signature of a small remotely operated vehicle for detection

We present a characterization of both the hydrodynamic flow associated with the motion of a small remotely operated vehicle (ROV) and the acoustic signature emitted from the ROV. We experimentally measure the acoustic signature of a commercial off-the-shelf mini ROV by recording the underwater sound with stationary hydrophones, simultaneously compared with measuring the flow fields with particle image velocimetry (PIV). By conducting the trials during a variety of ROV maneuvers, we quantify the most underlying mechanisms that generate the ROV acoustic signatures which include the electric motor signal, propeller induced signal, pressure fluctuation due to the propeller wash and emission induced by flow over the ROV body. From the experimental results, we conclude that the electric motor is the main source of acoustic signature. The dominant acoustic frequency is between 70 Hz to 80 Hz with sound pressure level of 146 dB re 1 μPa at 1 m. Based on this characterization, we predict the feasibility of the detection of a small ROV using a model for transmission loss to predict the influences of attenuation and spreading. The predictions of detecting performance are based on a signal-to-noise ratio (SNR) for typical environments: shallow coastal water, ports and harbors, and deep oceans. Based on these models, we can quantify potentially the effective range of passive detection of underwater vehicle in the three distractive environments.

[1]  Hongyan Li,et al.  Motor noise source identification based on frequency domain analysis , 2009, 2009 International Conference on Mechatronics and Automation.

[2]  R. Adrian Particle-Imaging Techniques for Experimental Fluid Mechanics , 1991 .

[3]  P. Vukadin,et al.  Measurement of vessel underwater noise signature , 2008, 2008 50th International Symposium ELMAR.

[4]  Alexander Sutin,et al.  Feature based passive acoustic detection of underwater threats , 2006, SPIE Defense + Commercial Sensing.

[5]  Soo Pieng Tan,et al.  Enabling humans to hear the direction of sounds underwater - Experiments and preliminary results , 2008, OCEANS 2008.

[6]  Gerardo G. Acosta,et al.  LOW-COST AUTONOMOUS UNDERWATER VEHICLE FOR UNDERWATER ACOUSTIC INSPECTIONS , 2009 .

[7]  Joe M. Cuschieri,et al.  Acoustic signature of an AUV , 2003 .

[8]  P. Arzelies,et al.  Underwater acoustic noise measurement in test tanks , 2000, IEEE Journal of Oceanic Engineering.

[9]  U. Tureli,et al.  Passive Acoustic Detection of Divers Using Single Hydrophone , 2006, 2006 Fortieth Asilomar Conference on Signals, Systems and Computers.

[10]  Robert J. Urick,et al.  Principles of underwater sound , 1975 .

[11]  R.K. Lennartsson,et al.  Passive acoustic detection and classification of divers in harbor environments , 2009, OCEANS 2009.

[12]  Alexander Sutin,et al.  Passive acoustic threat detection in estuarine environments , 2008, SPIE Defense + Commercial Sensing.

[13]  Stewart A. L. Glegg,et al.  A passive sonar system based on an autonomous underwater vehicle , 2001 .