IEEE Circuits and Systems Magazine - Q1 2022 - 50

wideband radar sensor for vital signs monitoring reported
in [55], where the digital controlled oscillator (DCO) with
embedded Domino chirp generation is leveraged to realize
fast chirp generation. The transmitted pulsed chirp signal
and the received output signal are shown on the right side
of Fig. 14. The received echoed radar signal is processed using
the de-chirping, bandpass filtering, and finally digitization
with an ADC [55]. A highly integrated chip-scale 6-channel
FMCW radar sensor with antenna-in-package for gesture recognition
and short-range communications has been devised
by Google and Infineon Inc. [78]. The diagram is illustrated
in Fig. 15, where the RF and analog front-end (AFE) circuits,
serial peripheral interface (SPI), and control modules are
integrated on-chip. Moreover, high data rate communication
can be implemented simultaneously based on the radar
chip. The receiver patch antennas own a combined antenna
gain of around 10 dBi, while each transmitter antenna is with
a gain of about 6 dBi. The transceiver chip contains an integrated
voltage-controlled oscillator (VCO) with a wide tuning
range, which can enable a measured phase noise lower than
−80 dBc/Hz at 100 kHz offset. The radar signal is processed by
artificial intelligence (AI)-assisted algorithms to realize cognitive
gesture recognition and accurate gaits classification [78].
Beam-steering and beamforming are implemented for
phased-array radars to scan the scenario. The de-chirped
IF signal's spectrum is leveraged to indicate the range between
the radar and the subject. The subject location can be
determined based on the azimuth angle and the range [81].
The respiration rate and heartbeat rate of the subject would
be monitored based on radar sensing [81]. Moreover, the
variations of the respiration rate and the heartbeat rate can
be detected, which is indicative of the status of the subject
and can be served as an alarm for monitoring chronic cardiovascular
diseases [3], [81]. To ensure precise vital signs
monitoring, random body movements of the subject need
to be calibrated adaptively. In [145], the extracted phase is
compensated by the camera recorded video to eliminate
the effects from random body movements. Furthermore, an
FMCW radar sensor can be used to identify human subjects
based on the obtained phase information. First, human
subjects are recognized based on the extracted vital signs.
Then, SAR imaging is applied to label the human targets in
Tx4
D4
DDS
PLL
Tx2
D2
D1
DDS
PLL
Tx1
DDS PLL
Tx Trigger
Rx LO Trigger
TOR Predictor
f
Mode 2
t
Rx4
θ
PGA + BPF (5 Stages)
Rx2
Rx1
Cascode
VGLNA
CS
Ant. 2
Ant. n
θ
∆τ = ∆τDLL + ∆τPS
=
Pant. × sinθ
C
Figure 10. Schematic of the phased-array X-band FMCW radar for SAR imaging [79] © 2018 IEEE.
50
IEEE CIRCUITS AND SYSTEMS MAGAZINE
FIRST QUARTER 2022
Predicted Time
of Return tTOR
n∆τ
LO for Stretch
Processing
∆τ ×C
Stretched
Output Occupy
Much Lower
Bandwidth
t
φ
Reference LO Generator
TOR
PA
LO Chirp PLL
Single Tone
PLL
f
Mode 1
t
Pant.
∆τ ×C
Fine Tune by
Phase Shifter
DLL_Dn
Tx Pulse n
(n-1)∆τPS
Ant. 1
θ
f
φ
PA
φ
PA
Coarse Delay
by DLL MPS
DLL_D1
Tx Pulse 1
DLL_D2
Tx Pulse 2
∆τDLL
∆τPS
Digital Beamforming
DLL Based MPS
Tx Pulse
From Ant. 1
Tx Pulse
From Ant. n
Rx Echo Arrive
at Ant. 1
Rx Echo Arrive
at Ant. n

IEEE Circuits and Systems Magazine - Q1 2022

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