1
DETECTION OF STATIONARY HUMANS USING
TIME-DIVISION UWB MIMO THROUGH-WALL
RADAR
Sun Xinxin
2
, Jin Liangnian
1,2*
, Liu Qinghua
2
1
Guangxi Key Lab of Wireless Wideband Communication &Signal Processing, Guilin 541004, China
2
Institute of Information and Communication , Guilin University of Electronic Technology, Guilin 541004,
China
*jing@guet.edu.cn
Keywords: STATIONARY HUMANS DETECTION, TIME-DIVISION UWB MIMO RADAR, MAXIMUM
COHERENCE COEFFICIENT, BAND-PASS INCOHERENCE COEFFICIENT
Abstract
Existing radars for stationary humans detection need to
process echo data from all channels simultaneously, which
requires the radar system with high performance. Another
limitation of existing technology is poor positioning due to
sidelobe interference. In this paper, a time-division
ultra-wideband (UWB) multiple-input-multiple-output
(MIMO) radar is presented for stationary human detection
using the incoherence of respiratory echoes. Based on the
delay-and-summation (DAS) imaging method, the maximum
coherence factor (MCF) is weighted to suppress sidelobe,
band-pass incoherence factor (BICF) is weighted to
distinguish stationary objects and human targets, and the
variance factor (VF) is weighted to achieves accurate
positioning. Experimental results show that this method can
effectively suppress the noise, filter off the echo of the
stationary object, and provide the distance and azimuth
information of hidden human targets accurately.
1 Introduction
Technology for UWB radar imaging is highly desired in
urban street fighting, disaster relief and anti-terrorism
reconnaissance, and so on [1], [2]. Technologies of
through-the-wall radar for human detection and recognition
mainly use the delay time of echo signal caused by the human
breathing and heartbeat to obtain the position information of
hidden human. Primitively, single-frequency continuous
wave radar is used to vital signs detection [3]-[5], which only
have the ability to determine whether there is a human or not,
but can’t provide the position information. As a solution,
UWB radar has been proved to be capable of providing
distance information with a high distance resolution. Both
distance and respiratory information of hidden human are
obtained by using single-channel ultra-wideband radar
[6]-[10]. However, single-channel UWB radars have no
ability of horizontal resolution so that it is not suitable for
detection and positioning of multiple human targets. In recent
years, multi-channel UWB radar has significantly advanced.
In [11], a two-dimensional antenna arrays is firstly used for
human targets detection and location. Subsequently, various
algorithms have been proposed in [12]-[14] to detect
respiration and heart rate, providing distance and azimuth
information effectively. Furthermore, the coherent
characteristics and incoherent characteristics of synthetic
aperture radar signals in [15] are used to distinguish
stationary objects and human targets. However, these
multi-channel UWB radars detection methods need to
simultaneously process the echo signals of all channels, so
requirements for the performance of the radar system are
higher. There are also many deficiencies such as poor
positioning and high sidelobe.
In this paper, a stationary human detection method using
time-division UWB MIMO radar is proposed. Firstly, DAS
imaging is performed on all channel echoes. Secondly, MCF
is used to eliminate sidelobe interference. We calculate the
corresponding BICF and VF of the channel data to
distinguish stationary objects and human targets. Finally, we
calculate the product of the DAS image, MCF, BICF, and VF
with appropriate weight to achieve imaging of stationary
human targets with low sidelobe. This method has a better
performance in human target positioning compared to the
generalized incoherence coefficient imaging algorithm (GICF)
proposed in [15].
2 Signal Model
The scene is illuminated by a time-division UWB MIMO
radar, assuming the number of transmit and receive antennas
are M and N respectively. The m-th transmitting antenna
transmits the impulse waveform
(with a peak point
), and the echo signal received by the n-th receiver can be
expressed as
, , , 0 , ,m n w m n w k m n k p m n p b
kp
s t x t x t x t
(1)
where the first term represents echo signal of the wall, and
represents the round-trip propagation delay. The second
term denotes the echo of stationary objects, and
is the
propagation delay of the electromagnetic wave between the
transceiver and the k-th
stationary object. The third term
indicates the echo signal of human targets, and
indicates the propagation delay between the transceiver and