Aerospace and Electronic Systems Magazine May 2018 - 14

Feature Article:

DOI. No. 10.1109/MAES.2018.170124

WiFi-Based Through-the-Wall Presence Detection of
Stationary and Moving Humans Analyzing the Doppler
Spectrum
Simone Di Domenico, Mauro De Sanctis, Ernestina Cianca, Marina Ruggieri
University of Rome Tor Vergata, Rome, Italy

INTRODUCTION
Through-the-wall (TTW) sensing is relevant in several scenarios.
In particular, a system able to detect the presence of a noncollaborative person behind a wall could be used by law enforcement for better planning actions in case of standoffs and hostage
situations. For emergency situations, first responders could use
such a system to detect the presence of people through rubble
and collapsed structures. Traditionally, these types of systems
have been designed using a radar approach. In particular, ultrawideband systems (2 GHz of bandwidth) have been proposed for
detecting human presence by using radio frequency (RF) signals
[1], [2]. These systems usually require a large power source and
big antennas. Recently, to reduce the power and complexity of
these devices, the use of opportunity signals, such as WiFi signals,
has been considered [3]-[6]. However, most of the mentioned approaches are still radar-like. For instance, in [4], they capture the
WiFi signals reflected by the body of a person moving behind the
wall, and by using inverse synthetic aperture radar processing,
they are able to track the person as he or she moves behind the
wall. Moreover, in this work, the WiFi transmitter is located close
to the wall, and it is not just an access point (AP) of opportunity.
A different device-free presence detection approach using WiFi
signals is based on the fact that the presence or activity of a human
being inside a room changes the propagation channel of the RF
signal and, in particular, the multipath characteristics. Therefore,
by studying how the channel varies over time, presence or activity
may be recognized [7], [8]. In most of these works, it is explicitly
mentioned that one advantage in using such RF signals is that they

enable also presence detection or activity recognition (AR) TTW.
Nevertheless, there are not many works on TTW presence detection and AR on the basis of WiFi signals and, more specifically,
on the use of channel state information (CSI). TTW RF sensing is
challenging for two main reasons:
1. The signal-to-noise ratio is lower.
2. The signal paths reflected by the human body are more unlikely to reach the receiver.
One work on the use of CSI from commodity WiFi devices for
TTW detection is presented in [3]. However, the proposed system
is only able to detect a person walking, even if slowly, in the room
behind the wall. However, the automatic detection of people in stationary positions, i.e., sitting or standing firm, is also important.
In this article, we present a TTW presence detection system for
both stationary and moving persons. The proposed system uses the
WiFi signal transmitted by a single WiFi AP. The assumption is that
in the case of an empty environment, with one stationary person or a
moving person in the room, the channel frequency response changes
over time in different ways. To understand how the channel frequency response varies over time, the mean Doppler spectrum computed
on the extracted CSI is used. The presence detection is then performed through a classification process applied to a selected set of
features calculated on the mean Doppler spectrum. Through experimental results, this article shows the feasibility and effectiveness of
the proposed approach for the detection of stationary humans, which
is usually rather challenging in TTW and non-TTW scenarios.

RELATED WORKS
Authors' current address: S. Di Domenico, M. De Sanctis, E.
Cianca, M. Ruggieri, Department of Electronics Engineering,
University of Rome, Tor Vergata, 00133 Rome, Italy, E-mail:
(mauro.de.sanctis@uniroma2.it). M. De Sanctis is also with the
Peoples' Friendship University of Russia (RUDN University), 6
Miklukho-Maklaya St, Moscow, 117198, Russian Federation.
Manuscript received June 15, 2017, revised October 31, 2017,
and ready for publication December 19, 2017.
Review handled by L. Ligthart.
0885/8985/18/$26.00 © 2018 IEEE
14

The first example of opportunistically using WiFi signals for human detection was presented in [9]. A TTW human detection system passively using WiFi signals was designed and implemented
in [5]. However, it can only detect line-of-sight people crossing
between the transmitter and receiver.
In [6], the feasibility of detecting people moving behind walls
by using passive bistatic WiFi radar at standoff distances is investigated. The experimental data were acquired by using University
College London's multistatic netted radar system that consists of

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MAY - JUNE 2018



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