IEEE Circuits and Systems Magazine - Q1 2021 - 54

Doppler speed and angle of the targets. In addition, outstanding progress using SISO FMCW radar is proposed
in [109] for remote 2-D localization of multiple subjects.
This contrasts the current state-of-the-art SISO approaches that can only provide only range information.
The authors in [60] and [16] proposed a novel chipbased radar for vital sign detection fabricated using
the 40 nm CMOS process technology. In this work, the
FMCW radar operated based on burst chirp, which is
generated using a digitally controlled oscillator (DCO)
structure with embedded domino chirp generation. A
time domain digital predistortion block is included in
the DCO to generate fast and linear chirps. Each block is
controlled by the finite state machine (FSM). The radar
has fat chirp slope of 0.7 GHz/40 ns with low RMS error
of 0.5 MHz. Due to the deactivation of all radar circuits
out of the burst-chirp duration, the power consumption was reduced more than 30 times to a record-low of
680 nW. This radar has the capability of detecting human respiration at a distance of 15 m and heart beat
detection at a distance of 5 m. The authors in [61] demonstrated the application of this chip on multi-people
tracking and vital sign detection. The frequency used
in FMCW radars ranges from an initial frequency and
is then swept over a period of time to arrive at the final
frequency. This process is repeated over multiple periods. Next, as illustrated in Table 5, a radar for detection applications is designed with a center frequency of
600 MHz and a bandwidth of 300 MHz in [52]. These frequencies will possibly be too low if a higher range resolution is needed, especially when potentially detecting
the small movements from the chest wall. The radar
used for RR and HR detection in [7] operates between
76 GHz and 81 GHz, offering a high range resolution.
Other operating frequencies include from as low as several gigahertz to as high as nearly 100 GHz [8], [51], [53].
D. SFCW Radar
SFCW operates by stepping the frequencies in the transmit signal, or by stepping randomly selected frequencies.
It can function approximately as an UWB radar in the frequency domain, and therefore has similar capabilities. Due
to the frequency step, compressive sensing can be applied
to this radar, which enables faster detection. In addition to
that, such radars do not require high sampling rate from
their ADCs. SFCW radars are also capable of target tracking
and multiple targets' detection. It also has higher SNR compared to the UWB radar. In comparison to FMCW, calibration of the signal distortion due to hardware imperfections
is simpler in SFCW radars. However, its main drawback is
that the data acquisition time to step over many frequencies is very high, and compressive sensing algorithms are
generally used to speed up this process [2].
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IEEE CIRCUITS AND SYSTEMS MAGAZINE

The research in [2] uses two types of radars, UWB
and SFCW. Despite the higher resolution range-timefrequency information featured by the UWB radar, it
suffers from low SNR. To overcome this, a phase-based
method to tackle the issue of low SNR during human
vital sign detection is proposed in [2] and [49]. The
work in [2] solves the issue of SFCW long data acquisition time. It is done by proposing a multi-channel SFCW
and using compressive sensing to randomly step only
through 20% of the original frequencies. The block diagrams of both types of radars are shown in Figure 12
and Figure 13, respectively.
Next, researchers in [9] presented the detection of
human heart and breathing signal using SFCW radar. In
this study, a hybrid approach of inhomogeneous object
to calculate the received signal from the human rib cage
and heart was employed. After that, Fourier analysis
was conducted to find heart rate and respiration rate.
The preliminary results show good agreement with
practical data. In [55], a MIMO SFCW radar was designed
to detect multiple humans via their vital signs. A signal
model of the vital signs was developed first, followed
by the detection method involving improving the SNR.
This is prior to the application of an enhanced imaging
algorithm to suppress clutter and mutual coupling. The
proposed radar configuration is shown in Figure 14.
The research in [56] studied the detection of human
signals behind walls using SFCW radar. The main issue
with this scenario is the substantial loss of signal energy
due to wall reflections. Thus, clutter reduction methods
were used to improve the detection accuracy of the vital
signs. On the other hand, the effects of different human
orientations and multiple humans in the environment
were studied using an SFCW radar in [57]. The human rib
cage model was adopted in this study. Finally, [58] presents an overview of the use of different radar types for
vital sign detection. It also discusses the results of using
SFCW radar, relative to reference measurements. The designed SFCW is comprised of direct digital synthesizer
(DDS), controlled by a complex programmable logic device (CPLD), phased locked loop (PLL) and a power amplifier feeding the transmit antenna. At the receiver side, the
antenna is connected to an LNA and an IQ demodulator.
This radar has two channels to minimize acquisition time
and more channels can be added with one master clock.
The results indicate errors of 0.1%, 0.3%, and 0.8% for RR
of a person at 1 m, 1.5 m, 2 m distances, respectively. For
HR results, the error was 0.4%, 0.1% and 0.4%, respectively.
SFCW radar uses a single tone in its transmitted signal, stepped in (sometimes random) frequency steps.
This is the reason why such radar eliminates the need
for ADC with high sampling frequency. The typical bandwidth for the SFCW radar ranges between 1 GHz and
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