Wi-Vi: See Through Walls with Wi-Fi Signals
Fadel Adib      Dina Katabi
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The objective of this paper is to enable a see-through-wall technology that is low-bandwidth, low-power, compact, and accessible to non-military entities. To this end, the project introduces Wi-Vi (Wi-Fi Vision), a see-through-wall device that employs Wi-Fi signals in the 2.4 GHz ISM band.

Why is Seeing Through Walls Possible?

The concept underlying seeing through opaque obstacles is similar to radar and sonar imaging. Specifically, when faced with a non-metallic wall, a fraction of the RF signal would penetrate the wall, reflect off objects and humans, and come back imprinted with a signature of what is inside a closed room. By capturing these reflections, we can image objects behind a wall.
Radar Principle

Why is Seeing Through Walls Challenging?

Building a device that can capture such reflections is difficult because the signal power after traversing the wall twice (in and out of the room) is reduced by three to five orders of magnitude . Even more challenging are the reflections from the wall itself, which are much stronger than the reflections from objects inside the room. Reflections off the wall overwhelm the receiver's analog to digital converter (ADC), preventing it from registering the minute variations due to reflections from objects behind the wall. This behavior is called the Flash Effect since it is analogous to how a mirror in front of a camera reflects the camera's flash and prevents it from capturing objects in the scene.

Multiple Antennas to Eliminate the Flash

Existing solutions eliminate the Flash Effect by separating reflections off the wall from reflections off the objects behind the wall based on their arrival time. To achieve this separation, these techniquer need to identify sub-nanosecond delays to filter the flash effect. Therefore, they require blasting power in multi-GHz of bandwidth, available only to the miliary.

To eliminate the flash effect without using GHz of bandwidth, Wi-Vi encodes its signal across multiple antennas to cancel out all static reflectors at the receive antenna. A Wi-Vi device has two transmit antennas and a single receive antenna. It operates in two stages. In the first stage, it measures the channels from each of its two transmit antennas to its receive antenna. In stage 2, the two transmit antennas use the channel measurements from stage 1 to null the signal at the receive antenna. Since wireless signals (including reflections) combine linearly over the medium, only reflections off objects that move between the two stages are captured in stage 2. We further refine this basic idea by introducing iterative nulling, which allows us to eliminate residual flash and the weaker reflections from static objects behind the wall.
MIMO Nulling

Tracking Human Motion

Wi-Vi also needs to track human motion without using a bulky antenna array. To that end, borrow a technique called inverse synthetic aperture radar (ISAR), which has been used for mapping the surfaces of the Earth and other planets. The technique works as follows: when a person moves, he reflects the transmitted signal from different points in space. We can conceptually think of the person as a moving antenna . The device captures consecutive time samples and treats them as consecutive spatial samples . Using standard antenna array processing, it is able to indentify the relative angle of the person's motion with respect to the device. We extend this method to track multiple humans by using the smoothed MUSIC algorithm .
Inverse SAR

A Through-Wall Gesture Interface

Wi-Vi leverages its ability to track motion to enable a through-wall gesture-based communication channel. Specifically, a human can communicate messages to a Wi-Vi receiver via gestures without carrying any wireless device. We have picked two simple body gestures to refer to '0' and '1' bits. A human behind a wall may use a short sequence of these gestures to send a message to Wi-Vi. After applying a matched filter, the message signal looks similar to standard BPSK encoding (a positive signal for a '1' bit, and a negative signal for a '0' bit) and can be decoded by considering the sign of the signal.

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