The Secrets Of Effective Communication

An acoustic signal is sent horizontally through ocean waters from one point to another. All along the way the sound is bouncing off a “ceiling” of choppy, wind-whipped seas and seafloor that could be craggy rock or smooth sand.

If researchers can understand better how physical conditions like these distort sound as it travels through the ocean, they could send data underwater faster and with less power and could make it much easier for networks of sensors to talk to each other simultaneously. They could improve wireless communications from commonly used ocean instruments such as Doppler current profilers and potentially eliminate the need for vehicles and gliders to surface just to transmit modest amounts of data.

With these goals on the horizon, a science team led by Scripps Institution of Oceanography at UC San Diego researchers completed in early July a three-week study of waters west of the Hawaiian island of Kauai. Scripps acoustician Bill Hodgkiss, principal investigator of the project lengthily known as the Kauai Acomms MURI Experiment, said the region was chosen for its dynamic characteristics.

“It goes from very calm to whitecap conditions every 24 hours and that repeats on a regular basis,” Hodgkiss said.

The research team, which included Scripps researchers Bill Kuperman, Heechun Song, and Bruce Cornuelle, and colleagues from UCSD, the University of Delaware, and Arizona State University, inventoried the suite of conditions that can disrupt a signal as it travels between two underwater points. The team made wind speed and surface wave measurements to gauge the structure of the sea surface and temperature profiles to estimate sound speed (the colder the water, the slower sound travels), and measured the topography of the seafloor.

Hodgkiss rated the experiment a major success and said its data should improve computer models used to guide development of underwater acoustic modems—especially for use in places less accessible than Kauai.

“This experiment should improve prediction of the fluctuation characteristics in other environments that you don’t necessarily have the resources to go and study,” Hodgkiss said.