IEEE Circuits and Systems Magazine - Q1 2021 - 69

opens opportunities of inventing novel solutions which
are capable of processing very complex algorithms to
meet the real-time detection requirements.
On the other hand, researchers are still investigating
new algorithms to maximize the detection accuracy, at
the expense of more complex algorithms. At the same
time, more detection scenarios are being experimentally assessed to validate these algorithms in practice.
It is demonstrated throughout the survey that the main
future trends in vital sign detection using radars is
geared towards enabling more practical methods for real-time detection. More practical (and yet challenging)
scenarios includes situations where vital signs need to
be detected from a person located in a crowded room
with multiple people, which is indirectly related to multipath detection. The introduced unwanted signals due
to random movements affects detection accuracy due
to the additional noise and interference. Other issues
include dc offset, coupling issues, position sensitivity,
amplitude and phase imbalance and circuits' linearity.
To solve these challenges, researchers have introduced
more sophisticated algorithms and complex approaches which are computationally-intensive [104]-[107].
Such computational requirements can naturally be
solved using parallel processing platforms. Other challenges related to circuit design, power consumption
etc. have also been addressed by different researchers
at different levels [16], [60], [108]. With the recent ad-

vances in CMOS processes and technologies, the new
challenge for these sophisticated miniaturized designs
will then be in terms of low power consumption, which
is becoming increasingly stringent. Moreover, the integration of different systems in one platform and interference between different systems are another set of
future challenges requiring future research focus. More
recently, artificial intelligence in the form of machine
learning methods have been introduced to enhance
detection accuracy. This brings great potential to the
research activities in this field and may enable early
warning of fatal situations such as a heart attack or
asthma attack [6].
SFCW radar is one of the radar types which have
gained the most preference in recent years in the application of vital signs monitoring and detection. The
different state-of-the-art literature where SFCW radar
was used for human vital sign detection and monitoring,
is summarized in Table 9. The articles listed in Table 9
proposed and implemented several algorithms to SFCW,
such as CFAR, morphological filtering, numerical method, Fourier transform, singular value decomposition
SVD, method of moments, fast multipole method, statespace method, and compressive sensing algorithms.
The authors in [55] validated the effectiveness of the
proposed algorithms to be used in a MIMO SFCW radar.
Through-wall detection of up to three adjacent human
subjects can be detected and discriminated based on

Table 9.
Summary of SFCW radar and algorithms used in literature.
Frequency
Spectrum

Ref.

Algorithms

Functions/ Advantages

[2]

* CS
* SSM

To reduce data acquisition time and to avoid producing inter-modulation
products in FFT

2-4 GHz

[9]

* FT and hybrid
numerical method
* MoM

To decompose inhomogeneous object into sub-homogenous domains
and detect the signal in simple way.

Not reported

[55]

* CFAR
* MFC

To suppress clutter and mutual coupling from multiple targets and to
improve weak signals.

40-4400 MHz

[56]

* SVD and MA

Clutter reduction techniques to improve detection accuracy.

1-3 GHz

[57]

* MoM parallel with
FMPM
* SSM

To accelerate computation time and extract the rate.

2-3 GHz

[58]

* CS

To avoid long data acquisition time.

2-4 GHz

Table abbreviations:
MFC: Morphological Filtering and Clustering
SVD: Singular Value Decomposition
MA: Moving Average
MoM: Method of Moment
FMPM: Fast Multipole Method
SSM: State Space Method

FIRST QUARTER 2021

IEEE CIRCUITS AND SYSTEMS MAGAZINE

IEEE Circuits and Systems Magazine - Q1 2021

Table of Contents for the Digital Edition of IEEE Circuits and Systems Magazine - Q1 2021