PICTURE the scene: a submarine edges through the cold, black waters beneath
the Arctic icecap. Visibility is zero. Anywhere ahead there could be a million
tonnes of ice, plunging down from the surface in a giant keel, ready to slice
the craft open. The crew could shine a searchlight into the gloom but it would
do little good because seawater absorbs light waves so well. Sound waves are a
better bet, but the captain dares not send out sonar pulses to locate the keels
for fear of attracting attention from hostile forces.
Or imagine marine biologists trying to study migrating whales. They want to
count the creatures swimming by. But the only way to detect them is to fire out
sonar pulses, and risk upsetting the whales鈥� in-built and highly sensitive sonar
systems.
These are just two of the kind of problems that Michael Buckingham, a
physicist from Scripps Institution of Oceanography in La Jolla, California,
believes he has solved. To him, the answer is as clear as daylight. He and his
colleagues John Potter and Chad Epifanio have developed a prototype underwater
viewing system called ADONIS, or acoustic daylight ocean noise imaging system.
Unlike sonar, ADONIS is completely passive, making use of the ambient noise that
already permeates the ocean.
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During the day, objects on dry land are bathed in sunlight. You can see a
tree, say, because it scatters some of this light in your direction. If you take
a photograph of a tree, you are focusing scattered light from the tree onto a
film. Buckingham鈥檚 idea is to do exactly the same thing with sound in the ocean:
pick up the background sound scattered by a target and use it to form an image
of the target using an array of underwater
microphones鈥攈ydrophones鈥攊nstead of a camera. Of course, there is no
acoustic equivalent of the Sun underwater, but the oceans are full of ambient
noise鈥攆rom ships, breaking waves, marine mammals, fish and rainfall.
Image problem
Though it sounds simple enough, Buckingham鈥檚 proposal made big waves among
his colleagues in the mid-1980s when he first aired it. Everyone knew about
ocean noise, but they saw it as a nuisance rather than a resource. The only ways
to detect something deep underwater were to track a target that was already
noisy鈥攁 marine mammal echo-locating, for instance鈥攐r to beam out a
sound pulse and listen for the echo. Either way, background noise just got in
the way.
With this as the mindset, Buckingham鈥檚 idea met with considerable scepticism.
The noise would not have enough energy to create good images, said his
critics鈥攖here would be too much scattering between the target and the
detector, and the signal would be too weak to give decent contrast. 鈥淢any people
thought it wouldn鈥檛 work,鈥� Buckingham says. 鈥淚t was very high 谤颈蝉办.鈥�
Nothing daunted, he did some calculations to convince himself that the system
could work. Next, he tried a sensor bearing a single hydrophone to confirm that
it could spot the presence of a target. Finally, in August 1994, he and his team
completed ADONIS. The system comprised a spherical reflector 3 metres across,
like a large satellite dish, which picked up the scattered sound waves and
focused them onto an array of 126 hydrophones. Each hydrophone created one
鈥減ixel鈥� of the eventual image, with the intensity of the noise signal from each
hydrophone showing up as the relative brightness of a point on a desktop
computer screen back on dry land (see
Diagram).
Mounting excitement
The team dropped ADONIS into the Pacific off the end of a pier at Point Loma
in San Diego. Their target was a frame 3 metres square, like the grid you use
for noughts and crosses, on which nine panels could be mounted to give different
patterns. First, the researchers tried a simple bar made from three panels in a
row. Sure enough, up on the screen came an unmistakable bar shape. The team鈥檚
nervousness, partly created by the scepticism of their colleagues, suddenly
lifted. 鈥淲e were so excited when we saw it,鈥� says Buckingham. 鈥淲e were stunned
that we saw anything at all.鈥�
Next, they became more ambitious鈥攕etting up a target with four panels
in a cross shape, leaving the middle panel empty. At a range of 38 metres, the
1-metre square hole in the middle was at the limit of ADONIS鈥檚 resolution. At
first, they could not pick out the hole, but eventually, after some extra data
processing, it appeared in the cross shape on screen.
Full of confidence, the team returned to the pier last autumn, this time
armed with an assortment of targets鈥攐il drums filled with sand, water or
foam, titanium spheres, panels backed with different kinds of rubber and with
varying degrees of corrugation to change their acoustic properties. Though
Buckingham and his team are still analysing the data from these tests, they have
already seen some of the advantages of the system in action. For instance, with
their study site handily close to the shipping lanes heading into San Diego,
they had plenty of opportunities to study what happened to their sound pictures
as ships passed by.
鈥淯sually if you have a ship come over the horizon it鈥檚 bad news鈥攊t鈥檚
competing with the signal that you want to see,鈥� says Buckingham. But with
ADONIS a passing ship is a positive advantage. 鈥淚t鈥檚 just more illumination.
It鈥檚 like a football game on a Saturday afternoon when it starts getting dark
and they turn on the floodlights.鈥�
On one occasion the team saw a target 鈥渓it鈥� from both front and back. A
passing ship generated low-frequency noise that 鈥渟hone鈥� behind the target,
casting it in relief. Meanwhile, high-frequency noise from snapping shrimp
lurking by the pier reflected off the front of the target and back into the
detector. So flicking from low to high frequency changed the image from dark to
light (see
Diagram below). Effects like this could make it easier to detect
objects, or might even give extra information about their composition and
acoustic properties.
A sharper picture
Now that the prototype is working well, Buckingham and his team are planning
ways to improve it. One of the biggest problems is resolution. The sharpness of
the images ADONIS produces is limited by the wavelength of the sound used and
the size of the focusing dish鈥攕horter wavelengths and a larger dish give a
higher resolution. But the sound waves used by Buckingham and his team are
around 10 000 times longer than light waves, so you would need an impracticably
large dish鈥攕everal hundred metres wide鈥攖o match the resolution you
get with light. In fact, the team is reluctant to increase the size of the dish
for fear of making it too cumbersome. Increasing the number of hydrophones in
the array would help, and the team is working on this now.
Another way to improve the resolution would be to look for scattered noise at
higher frequencies, with shorter wavelengths. The problem here is that there is
a trade-off between resolution and range. The shorter the wavelength of sound,
the better water is at absorbing its energy, which limits the range of the
system. Buckingham and his colleagues have tried sound waves ranging from 8 to
80 kilohertz. At about 20 kilohertz, Buckingham estimates that the signal would
disappear completely if the object being viewed were more than a kilometre away.
For the highest frequency, it鈥檚 more like half a kilometre.
鈥淚t鈥檚 like working in a mist. You can see up to a certain distance and then
the mist cuts in,鈥� he says. The ultimate solution, he says, may be to tailor the
wavelength to give different resolutions and ranges for different applications.
Arctic submarines, for example, might want a longer range and settle for poorer
resolution. By contrast, a short-range, high-resolution application could be
mine detection. Mines are notoriously difficult to detect, especially if they
are partially buried near a shore. Acoustic daylight imaging has already managed
to detect partially buried objects such as oil drums. What鈥檚 more, says
Buckingham, 鈥渋f the mine happens to be intelligent and knows that somebody is
pinging at it, it might detonate. This system is covert, so you avoid that
谤颈蝉办.鈥�
Another improvement would be to employ an electronic trick called a phased
array. With the present system, if you want to scan in different directions you
need to change the orientation of the dish. But with a phased array you could
scan a range of angles electronically rather than physically. It works like
this. If a vertical wavefront hits a vertical row of detectors, they all
register its arrival at exactly the same time. If a wavefront comes in at an
angle, however, different detectors will record its arrival at different times.
So by pre-programming the detectors with the arrival times of the
wavefront鈥攕o that each one registers only the signal that arrives after
the appropriate time delay鈥攜ou can pick up signals coming from that
direction. Prime the detectors with several sets of time delays and you have a
neat way of scanning for sounds in different directions without having to move
the array physically.
Using this approach means you don鈥檛 even need a dish. Buckingham imagines a
submarine with hydrophones embedded in its body. Based on the shape of the sub,
you could program appropriate time delays into the hydrophones to convert their
signals into a coherent image. 鈥淭he skin of the vehicle could be the sensor,鈥�
says Buckingham. 鈥淵ou鈥檇 have a roving eyeball.鈥�
One of the biggest surprises to emerge from the field of acoustic imaging is
that there may already be a biological version of ADONIS. Experiments conducted
more than 15 years ago turned up intriguing evidence that some marine mammals
may use acoustic daylight imaging as well as sonar to find their way around. In
the experiments, porpoises seemed to be able to track the movement of fish even
without sending out sonar pulses. The results could not be explained, and were
simply pushed to one side. Buckingham now hopes to collaborate with Ann Bowles
of the Hubbs SeaWorld Research Institute in California to see whether killer
whales can do the same. It may turn out that, once again, nature is way ahead of
us in the technology stakes.