Tracking WiFi signals to passively see through walls using NI USRP and LabVIEW

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With dedication and a creative approach, University College London (UCL) research is helping to address the world's most urgent problems. Whether designing healthier cities or grappling with issues such as global health and climate change, the challenges of daily life inspire UCL students and academics. Based at UCL, our team of electrical engineering researchers is investigating passive radar technologies that can see through walls using WiFi radio waves.

Our novel research required a real-time, passive (non-cooperative) wireless target detection demonstration system capable of tracking moving bodies through walls and obstacles. Much like traditional radar systems, our approach still relies on detecting the Doppler shifts in radio waves as they reflect off moving objects. However, unlike traditional radar systems that actively transmit radio waves, our passive system relies on the existing WiFi signals that already swamp our airwaves. The complete lack of spectrum occupation and power emission ensures our radar is undetectable, making it ideal for military or security surveillance in urban settings.

Aside from public defence applications, our passive detection could be applied in a broad range of scenarios, including crowd and traffic monitoring and human-machine interfacing. Different types of wireless signals can be applied to different situations. For example, our system could acquire IEEE 802.11x (b, g, n, ac) signals to detect indoor moving targets for security purposes, such as hostage situations. Alternatively, the same system could monitor cellular signals, such as Global System for Mobile Communications (GSM) or Long-Term Evolution (LTE), to detect direction and velocity of moving vehicles before triggering an appropriate machine response to the detected movement.

Maximising the versatility of our devised radar system requires multiple channels for compatibility with multiple frequency bands. The system should be flexible enough to work with almost any type of WiFi signal (IEEE 802.11 b, g, n, ac), as well as FM and cellular signals. This relies on flexible RF hardware that can accommodate wide frequency ranges, in addition to easily reconfigured signal-processing software.

Passive Wireless Detection System Based on USRPs

At the heart of our system were two USRP-2921 RF transceivers used to receive the reference and surveillance signals. Not only did the USRPs meet our accuracy and frequency range requirements, but their software-defined nature helped us rapidly iterate our algorithm designs.

From a software perspective, we chose LabVIEW as being an inherently multithreading development tool; it naturally reduced our code complexity. This, combined with other features of LabVIEW, including intuitive graphical programming and built-in design patterns, reduced our development time by weeks.

The NI USRP platform is available on multiple frequency bands, covering 50 MHz to 5.9 GHz, so our passive radar system could cover a huge range of wireless signals, including FM, GSM, LTE, IEEE 802.11x, IEEE 802.16, and digital audio broadcasting (DAB) or digital video broadcasting (DVB).

Besides wide-frequency band coverage, another advantage of USRP is that it includes a dedicated port for daisy-chaining and synchronising advanced multiple input, multiple output (MIMO) systems. This will be very useful as we extend the radar system for future research.

To program the USRP, LabVIEW provides an API that allowed us to quickly open, configure and initiate receiver sessions; set parameters such as centre frequency, IQ sampling rate, channel gain, and length of samples; and receive data from the air.

With USRP and LabVIEW, we built and tested the passive wireless detection demo very quickly. Using functions built into LabVIEW, we can efficiently implement a series of vector operations, such as array subset, indexing array, array reshaping and analysis, in a single block.

Proving the Concept with Real-World Experimentation

The scenario to demonstrate the capabilities of the designed system is to detect a walking person using WiFi signal emissions from a common WiFi access point (AP) which has 15dBm. In the experimental setup, a 25cm-thick brick wall separated the reference and surveillance antenna from the person and the WiFi AP (see Figure 3). Both reference and surveillance signals are digitised by the USRPs and processed in LabVIEW.

Experimental results gained via our USRP-based radar system have definitely proven the concept of through-wall passive WiFi sensing. In addition, with the high sensitivity of the NI solution, we can detect smaller movements than we initially thought possible.


LabVIEW and NI USRP are an ideal choice for rapidly prototyping wireless signal transmission, reception and processing. The wide frequency bands and ready-made signal processing libraries helped speed up code development and real-world experimentation.

We are truly excited about how our novel approach to passive radar can be used in the future, including public security (hijack or hostage situations), eHealth (a monitoring system for the aged) and new human-machine interfacing (for both industry and entertainment).

Aside from being a strong proof of concept, our demonstrative passive detection system will be used as a highly engaging teaching platform for engineering students and a testbed for future passive detection algorithm development.

Author profile:
Bo Tan - University College London

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