DetectionWi-Fi signals enable through-wall detection
Engineers prove the concept that local Wi-Fi signals can be used to monitor moving objects and bodies that are otherwise visually obscured. Although fundamentally similar to traditional radar systems, their novel approach is entirely passive — utilizing the wireless signals that already swamp our urban airways. This technology has a wide range of applications from healthcare monitoring, security and emergency disaster relief, to finding earthquake survivors in fallen buildings.
The innovative Wi-Fi Through-Wall Detection technology, developed by Professor Karl Woodbridge of University College London, was a finalist in the National Instruments (NI) Engineering Impact Awards which took place on 3 November 2014. The award competition, organized by National Instruments, honor engineers and scientists who, using graphical system design, are addressing some of the most challenging engineering problems and improving the world around us.
Professor Woodbridge and his team including Dr. Kevin Chetty and Dr. Bo Tan were one of two finalists in the “Advanced Research” category. The UCL team has proved the concept that local Wi-Fi signals can be used to monitor moving objects and bodies that are otherwise visually obscured. Although fundamentally similar to traditional radar systems, their novel approach is entirely passive — utilizing the wireless signals that already swamp our urban airways. This technology has a wide range of applications from healthcare monitoring, security and emergency disaster relief, to finding earthquake survivors in fallen buildings.
A UCL release reports that the team produced a patented passive radar system using multiple NI Universal Software Radio Peripherals (USRPs) and LabVIEW to fuel their cutting-edge research. The USRPs, which can operate over wide frequency bands, acquire radio frequency (RF) signals on several channels. They used LabVIEW to design and iterate the advanced signal processing used to detect minute Doppler shifts in the acquired wireless signals to sense movement.
For a case study about the technology and further information about the other finalists, see here. For more information about collaboration and innovation at UCL, you may like to read the case study brochure.
