A NEW type of radar which harnesses chaos theory can see clearly through walls and could help find survivors in disasters. The technology could also make on-board radar a practical proposition for cars.
Ultra-wideband (UWB) radar is already used to “see” through walls. It can detect the presence of people on the other side of a barrier by distortions to the reflected radio waves caused by their breathing or heartbeat. However, the radar returns are often cluttered by interference, obscuring the signal.
Now, Henry Leung and colleagues at the University of Calgary in Alberta, Canada, have found a way to sharpen the signal, which gets lost among multiple reflections within walls, known as reverberation, and by returns bouncing back via different routes.
Existing UWB radars typically use a random noise signal to avoid interference between waves of the same wavelength. But because the outgoing signal is not known it takes more processing to match it to the return. A second approach is to use a wide range of sequential frequencies; this is easier to match but more prone to interference.
Leung’s team are using a “chaotic oscillator” to generate their signal. The device creates what seems like random noise, but which is actually generated by a fixed algorithm. It is matched by a receiver using the same algorithm. Because the outgoing signal is known, it is as easy to process as spread-spectrum signals. It is also irregular, like random noise, meaning reflections are less likely to interfere with each other.
In tests, the chaotic signal produced better results than the other approaches. “It captures the desired properties of these two systems,” says Leung. This means the radar can see reliably through more layers.
Leung’s colleagues suggest that chaos radar could be used as an on-board sensor for vehicles as part of a smart traffic-management system. As chaos signals do not interfere with each other, many could operate in the same area.
Karl Woodbridge, who researches radar systems at University College London, warns that there may be some way to go before practical hardware emerges. “There are many complications in a real-world scenario which are not easy to predict in simulations.”