“Most technologies that can see through walls use a broad range of frequencies, which makes them expensive,” said Daniel Marks, associate research professor of electrical and computer engineering at Duke. “They also don't have very good resolution. So, while they might be fine for seeing a person moving on the other side of a wall, they're terrible for finding thin conduits or wires.”
Current approaches also typically rely on knowing what material the wall is made from before trying to see through it. This allows the software to predict how the wall will affect the scanning waves so that it can separate the echoes and distortions from the solid objects being sought.
Prof Marks and his colleagues take advantage of a wall's symmetry instead.
Because walls are generally flat and uniform in all directions, they distort waves in a symmetrical fashion. The Duke teams’ technology uses this symmetry to its advantage.
“We wrote an algorithm that separates the data into parts -- one that shows circular symmetry and another that doesn’t,” explained Okan Yurduseven, a postdoctoral researcher in electrical and computer engineering at Duke. “The data that doesn't have any symmetry is what we're trying to see.”
The technique uses only a single frequency to scan because it cuts down on the number of interference patterns created by the wall and single-frequency emitters are much less expensive than broadband emitters. Sticking to a narrow range also avoids interfering with microwave frequencies dedicated to other technologies, such as Wi-Fi, cellular phone service and Bluetooth.
The researchers built a prototype device to see how well it would work. They constructed different kinds of walls and placed objects like studs, electrical conduits, wires and junction boxes behind them.
Looking at the raw data after scanning through gypsum plasterboard, it’s difficult to make out anything other than a metal junction box, which is 4 inches wide and 2 inches thick. But after analysing the data and removing the symmetrical patterns, the pictures clear considerably, and each individual component is easily recognised.
“We envision combining this technique with a machine vision system that someone could move over a wall to see what's inside,” said Prof Marks. “We think the technology has the price point and sensitivity to make an impact on the market.”
