Transcript 2012 IEEE Radar Conference, May 7-11, Atlanta

Department of Information Engineering
University of Pisa
.
TUTORIAL
RF and Digital Components for Highly-Integrated
Low-Power RADAR
Sergio Saponara & Maria S. Greco
2012 IEEE Radar Conference, May 7-11, Atlanta
Speakers
Sergio Saponara is Associate Professor of Electronics
Maria S. Greco is Associate Professor of Telecomunications
both at the
Department of Information Engineering
University of Pisa, via G. Caruso 16, 56122, Pisa, Italy
[email protected], [email protected]
2012 IEEE Radar Conference, May 7-11, Atlanta
Outline of the tutorial
Scenarios and applications for highly-integrated
low-power RADAR
RADAR architecture and analog-digital
partitioning
RF/mm-Wave RADAR transceivers and ADC
Ubiquitous low-power RADAR case studies:
vital sign detection, automotive driver assistance
Digital signal processing for RADAR
HW-SW implementing platforms for RADAR
digital signal processing
Conclusions
2012 IEEE Radar Conference, May 7-11, Atlanta
Outline of the tutorial
Scenarios and applications for highly-integrated
low-power RADAR
RADAR architecture and analog-digital
partitioning
RF/mm-Wave RADAR transceivers and ADC
Ubiquitous low-power RADAR case studies:
vital sign detection, automotive driver assistance
Digital signal processing for RADAR
HW-SW implementing platforms for RADAR
digital signal processing
Conclusions
2012 IEEE Radar Conference, May 7-11, Atlanta
The semiconductor components market is growing..
…driven by highly integrated digital-based
ubiquitous systems realized in standard
Silicon (Si)-based technologies..
Source: iSuppli
2012 IEEE Radar Conference, May 7-11, Atlanta
Technology evolution driven by large volume
HW-SW systems addressing societal needs
(health care, energy, security, safety, intelligent
transport..)
Source: World Semiconductor Trade Statistics
2012 IEEE Radar Conference, May 7-11, Atlanta
Electronics evolution
Not only nanoscale CMOS but also System-in-Package
integration of passives, RF & mm-Wave, high voltage,
sensors/actuators (MEMS) ..
2012 IEEE Radar Conference, May 7-11, Atlanta
Ubiquitous RADAR applications
Although RADAR development was pushed by military applications in II
world war with high-power, large size and long-distance systems, today the
RADAR is becoming an ubiquitous technology adopted for:
Safer transport systems in automotive (automatic cruise control, urban
traffic warning, parking aid, obstacle detection), railway (crossing
monitoring, obstacle detection), ships
Info-mobility in urban, airport or port scenarios
Civil engineering, (static and dynamic structural health monitoring,
landslide monitoring, ground penetration for detecting pipes, electric
lines,….)
Distributed surveillance systems (smart cities, airports, banks, schools)
mm-wave body scanner for security
2012 IEEE Radar Conference, May 7-11, Atlanta
Ubiquitous RADAR applications
Remote bio-signal detection for health care (heart rate, breath rate)
Elderly/infant
syndrome,..)
assistance
(fall
detection,
sudden
infant
death
Civil protection (e.g. detection of buried people in case of earthquakes,
or under the snow after an avalanche or other natural disasters, or even
in war scenarios)
Contactless industrial measurements and in harsh environments
Through-wall target detection
RADAR sensing is suited to address societal needs of
safety, security, health-care, intelligent transport
2012 IEEE Radar Conference, May 7-11, Atlanta
Ubiquitous highly-integrated low-power
RADAR
RADAR can become ubiquitous adopted as sensing system for large
volume applications?
RADAR as EM sensor can offer big advantages for large volume highly
integrated applications w.r.t. other technologies:
operations in all weather and bad light conditions
contactless sensing and no line of sight sensing
non ionizing radiations
ground penetrating capabilities
multi parameter sensing (target detection,
speed,May
angles)
2012 IEEEdistance,
Radar Conference,
7-11, Atlanta
Ubiquitous RADAR design needs
With respect to conventional RADARs for defense and civil applications,
with large transmitted-power x antenna aperture product, the realization of
highly-integrated RADARs with low power consumption, size, weight and
cost is needed to enable its ubiquitous adoption in large–volume markets
Transmitted Power < 10-15 dBm
Short wavelength for miniaturization (3.9 mm@77 GHz)
Range from < 1m to < 100-200 m
Detection also with low SNR of 10-20 dB
Cross section from tens of cm2 to m2
Pt Gt Gr 2
Pr 
(4 ) 3 R 4
DSP techniques to improve performance and solve range-speed
ambiguities
Receiver sensitivity down to -100 dBm
Multiple channels may be used for channel diversity gain
2012 IEEE Radar Conference, May 7-11, Atlanta
Ubiquitous RADAR design needs
Key enabling factor for the success of this scenario is the realization, in
Si-based standard technologies, rather than using niche market
dedicated technologies, of integrated transceivers for the RF radar frontend and the implementation of computing intensive RADAR signal
processing algorithms in cost-effective and power-efficient embedded
platforms
Advanced concepts for System-in-Package integration have to be
explored
2012 IEEE Radar Conference, May 7-11, Atlanta
Frequency bands for highly integrated
ubiquitous RADAR
At high frequencies (short wavelengths
of few mm) there is potential for high
miniaturization, even the antenna
integration
thanks to technology scaling Si-based
technologies are offering good
characteristics at microwaves and mmWaves
2012 IEEE Radar Conference, May 7-11, Atlanta
Opportunities at mm-Waves
Compared with visible light and infrared, a RADAR offers lower attenuation
in bad weather and bad light conditions
Due to high attenuation 60 GHz band (V Band) reserved for short
communication s
At 77-81 GHz (W band) good opportunities for both LRR and SRR in mmWave domain
2012 IEEE Radar Conference, May 7-11, Atlanta
Outline of the tutorial
Scenarios and applications for highly-integrated
low-power RADAR
RADAR architecture and analog-digital
partitioning
RF/mm-Wave RADAR transceivers and ADC
Ubiquitous low-power RADAR case studies:
vital sign detection, automotive driver assistance
Digital signal processing for RADAR
HW-SW implementing platforms for RADAR
digital signal processing
Conclusions
2012 IEEE Radar Conference, May 7-11, Atlanta
Example architectures for integrated
RADAR systems
RADAR as a mixed analog-digital system
Pulsed RADAR with homodyne receiver
Pulsed RADAR with super-heterodyne receiver
Pulsed RADAR with correlator-type receiver
From analog to digital down-conversion
FMCW RADAR with digital down-conversion
Direct digital receiver
2012 IEEE Radar Conference, May 7-11, Atlanta
RADAR as a mixed analog-digital signal
system
DIGITAL
DOMAIN
(RX signal
processing, TX
waveform gener, LO
synthesis, user
interface, antenna
switch control)
ADC
DAC
ANALOG
DOMAIN
(PA, LNA, AGC,
FILT, T/R
SWITCH,
MIXER)
To the vehicle network
2012 IEEE Radar Conference, May 7-11, Atlanta
Pulsed RADAR architecture
with homodyne type receiver
Periodic transmission of a train of pulses of peak power Pt with fpr
(frequency pulse repetition), transmitted Pavg depends on duty cycle
In integrated systems high peak power can be problematic  limit on
duty cycling to achieve acceptable range performance
ToF analysis of the received echo pulses for target detection
2012 IEEE Radar Conference, May 7-11, Atlanta
Pulsed RADAR architecture
Easier on-chip integration of homodyne vs. a heterodyne architecture
avoiding selective passive filters at high frequencies
Antenna array used in timed-division for TX and RX (T/R antenna
switch needed, also for LNA protection from PA out)
A/D and D/A converters (ADC, DAC)
To reduce distortions DAC has to be of PAM type rather than PWM
(used in MCU)
ADC can operate at baseband (LO for I and Q down-conversion has
the same RADAR central frequency) or at IF
Signal processing (waveform generation, pulse compression, filtering,
range-speed ambiguities resolutions, CFAR detection, tracking) done
in the digital domain
2012 IEEE Radar Conference, May 7-11, Atlanta
Heterodyne-receiver alternative
By sharing the conversion requirements among different blocks
operating at different frequencies, RF, IF, baseband better performance
can be achieved
Selective passive filters at high frequencies (e.g. for image frequency
rejection). On-chip or in-package integrated selective filters today
possible
2012 IEEE Radar Conference, May 7-11, Atlanta
Trend from analog down-conversion …
IF or RF input at the quadrature down-conversion system depending if
homodyne or heterodyne receiver is used
2012 IEEE Radar Conference, May 7-11, Atlanta
.. to digital down-conversion
ADC operating at IF with digital based down-conversion (Numeric
Controller Oscillator –NCO- needed plus digital decimation)
2012 IEEE Radar Conference, May 7-11, Atlanta
FM-CW RADAR
f
Target
VCO
Quartz
Osc
fref
Phase
det.
t
Loop
filter
PA
R
Freq. divider
Interface
User I/O
77 GHz
TOF=2R/c
LO
Modulation
control (B, Tm)
X
LNA
RF
f TX
RX
DSP
FFT &
logic
ADC
amp
f fbeat
fbeat
 TOF
t
t
Received signal at the ADC
2012 IEEE Radar Conference, May 7-11, Atlanta
FM-CW RADAR
Separate antenna used for TX and RX due to continuous wave
Range and relative speed detection from batiment frequency analysis
(with FFT in digital domain)
The FMCW sweep frequency B and the time sweep Tm determine the
achievable range and speed resolution
Stable frequency synthesis based on PLL+VCO in analog domain
used in TX
ADC can operate at baseband or at IF
Signal processing and control (FMCW modulation control, filtering,
FFT, range-speed ambiguities resolutions, CFAR detection, tracking)
done in the digital domain
2012 IEEE Radar Conference, May 7-11, Atlanta
UWB Pulsed RADAR with correlatortype receiver
2012 IEEE Radar Conference, May 7-11, Atlanta
Receiver-type correlation
The received pulse echo signal, amplified by the LNA is multiplied with
a delayed replica of the transmitted pulses generated on-chip by a
Shaper circuit and integrated in the analog domain (low-rate ADC
needed) or in the digital one (high-rate ADC needed)
The amplitude of the signal at the output of the multiplier is related to
the target position
Averaging a large number of pulses allows us to increase the SNR,
depending on integrator bandwidth and pulse repetition frequency
SNRimp
f PR
 10  log(
)
Bint
2012 IEEE Radar Conference, May 7-11, Atlanta
RADAR with direct digital receiver
Aiming at a Software Defined Radio, in wireless communication
industry there is lot of interest on direct digital receiver where the
ADC is moving towards the antenna.
The dream is that all signal processing (apart antenna impedance
matching and first amplification) is done in the digital domain and is
fully programmable/configurable
What’s for RADAR?
2012 IEEE Radar Conference, May 7-11, Atlanta
RADAR with direct digital receiver
At least the LNA + RF Filter before the ADC is needed for optimal
impedance antenna matching, receiver Noise Figure, out-of-band
interference reduction, and to adapt the weak receiver signals to the
dynamic range of the high-speed ADC
The mixer could be removed at UHF, L or S RADAR bands since
Nyquist-rate ADCs exist capable of several GS/s
The limit is that high-speed low-power ADC have low dynamic range
(typ 5-6 ENOB) posing a limit to RADAR needing wider bit range to
face clutter
High speed DSP needs high data transfer and storage (large memory
size) and high clock frequency thus increasing power consumption
High speed medium/high dynamic range ADC needs high power
consumption and hence a mixer should be reintroduced
2012 IEEE Radar Conference, May 7-11, Atlanta
Main HW RADAR sub-blocks in analog
domain
Low Noise Amplifier
Antenna switch
Power Amplifier
Mixer
Adaptive Gain Control (AGC) amplifier
Phase Locked Loop (PLL), Voltage Controlled Oscillator, Quartz
Oscillator, phase detectors, phase shifter, frequency dividers
Baseband amplifiers and filters
Integrators
2012 IEEE Radar Conference, May 7-11, Atlanta
Main HW RADAR sub-blocks in digital
domain
ADC
DAC
Numerical Controller Oscillator (NCO)
Digital Delay Locked Loop (DLL), Digital Clock Manager (DCM)
Fast Fourier Transformer
Digital filters
Direct Digital Synthesis (DDS) for waveform generation
Other DSP blocks
User interface
Networking interface
2012 IEEE Radar Conference, May 7-11, Atlanta
RADAR Architectures –Bibliography
M. Skolnik, Radar Handbook, 3d Ed, McGraw Hill 2008
M. Skolnik, Introduction to radar systems, McGraw Hill
J. Hasch et al., Millimeter-Wave Technology for Automotive Radar Sensors in the 77 GHz
Frequency Band, IEEE Tran. Micr Theory and Tech, 2012
Y.-A. Li et al., A fully integrated 77 GHz FMCW radar transciever in 65 nm CMOS, technology
IEEE J. Solid-State Circuits 2010
C. Li et al., High-Sensitivity Software-Configurable 5.8-GHz Radar Sensor Receiver Chip in
0.13um CMOS for Noncontact Vital Sign Detection, IEEE Tran. Micr. Theory Tech 2010
D. Zito et al., SoC CMOS UWB pulse radar sensor for contactless respiratory rate monitoring,
IEEE Tran. Biomedical Circuits and Systems 2011
S. Saponara, B. Neri et al, Integrated 60 GHz Antenna, LNA and Fast ADC Architecture for
Embedded Systems with Wireless Gbit Connectivity, Journal Circuit Systems Computers 2012
B. Neri, S. Saponara, Advances in Technologies, Architectures and Applications of HighlyIntegrated Low-power Radars, IEEE Aerospace Electr. Syt. Mag. 2012
2012 IEEE Radar Conference, May 7-11, Atlanta
Outline of the tutorial
Scenarios and applications for highly-integrated
low-power RADAR
RADAR architecture and analog-digital
partitioning
RF/mm-Wave RADAR transceivers and ADC
Ubiquitous low-power RADAR case studies:
vital sign detection, automotive driver assistance
Digital signal processing for RADAR
HW-SW implementing platforms for RADAR
digital signal processing
Conclusions
2012 IEEE Radar Conference, May 7-11, Atlanta
Integration levels and technologies for
RADAR transceiver and ADC
Radar integration levels
System-on-board, -in-package, -on-chip
Integrated antenna
Technologies for integrated RADAR
III-V Transceiver
SiGe Transceiver
CMOS Transceiver
ADC
2012 IEEE Radar Conference, May 7-11, Atlanta
RADAR integration levels
Different levels of integration are possible for low-power RADARs
from single-board to single-chip systems with increasing
miniaturization but also increased technology complexity
System-on-a-single-Chip (SoC) where
completely contained in a single chip
the
RADAR
is
System-in-a-Package (SiP) where the RADAR is realized using
multiple chips but embedded in a single package
Single-board RADAR where the system is realized using
multiple integrated circuits mounted on a single board
2012 IEEE Radar Conference, May 7-11, Atlanta
Pro/Con of RADAR integration
Pro of Highly Integrated RADAR
Component assembly is minimized thus reducing cost and increasing
reliability and operating lifetime
Small size, small weight, low power consumption
Increased reproducibility and lower cost for large volume production
Con of Highly Integrated RADAR
IC design has high Non Recurring Costs (CAD tools and foundry cost,
design time and team design cost)  cost is minimized only for large
volume production
A single technology can not offer optimal performance for all RADAR
subsystems (CMOS optimal for baseband DSP, not for antenna design
or RF power amplifiers or for mm-Wave analog design)
Low transmit power limits possible applications to short range ones
2012 IEEE Radar Conference, May 7-11, Atlanta
RADAR-System-on-a-Board
RADAR with high transmit power and large aperture antenna are
realized by assembling multiple electronic boards, each optimized
for a RADAR subsystem: antenna subsystem with feed, reflectors,
and scanning modules, TWT or Klystron as Power Amplifier
modules, MMIC for TX/RX module, multiple boards for digitization
and RADAR signal processing, User Interface and networking
The next step, for low-power ubiquitous RADAR, is
assembling
all sub-systems on the same single printed circuit board (PCB)
2012 IEEE Radar Conference, May 7-11, Atlanta
RADAR-System-on-a-Board
RADAR-System-on-a-Board will assembly on the same board
- a single chip of a few mm2 integrating the whole TX and RX chains
operating in the RF or mm-Wave domain (CMOS or SiGe or MMIC in
III-V technologies)
- Solid-state power amplifier (depending on the transmit power needed)
- a single chip for baseband digital signal processing (DSP, FPGA or
custom IC in CMOS tech.): waveform generation, matched-filtered,
pulse compression, range/speed ambiguities resolution, CFAR…
- Memory modules (RAM and NV)
- ADC/DAC module (if not integrated in the custom IC, CMOS tech.)
- antenna (printed on the PCB board if gain, beam-width are enough..)
2012 IEEE Radar Conference, May 7-11, Atlanta
RADAR-System-on-Chip or in-Package
Thanks to submicron technology scaling CMOS is providing good
performance also for RF and mm-Wave low-power transceivers
The trend for the future is further increasing the miniaturization level
by integrating single-chip the RADAR transceiver plus the A/D and
D/A converters and part of the DSP chain, such as an FFT processor
CMOS SOI offers further improved performance at high frequencies
and for the realization also of passive components (inductors,
capacitors, even V/W bands antennas if few dB gain are enough)
Only the power amplifier and the antenna will be off-chip
2012 IEEE Radar Conference, May 7-11, Atlanta
RADAR-System-on-a-Chip or in-Package
Unless very low power and low antenna gain are required SiP is a more
viable solution for RADAR than fully SoC
2012 IEEE Radar Conference, May 7-11, Atlanta
System-in-Package Technology Options
- Different System-in-Package technology options available or under
research for mm-wave low-power RADAR or radio applications:
- Integrated substrate and/or Multi Chip Module (MCM), even 3D
Huei Wang , IEEE SIRF 2010
2012 IEEE Radar Conference, May 7-11, Atlanta
Integrated antennas
Towards high miniaturized systems the trend is integrating the antenna
- at board level (printed antenna on PCB boards)
- at package level (e.g. using Low Temperature Co-fired Ceramic LTCC
technology to realize multi-layer circuits with integrated passive
components including the antenna)
- at chip level using MMIC or Silicon on Insulator technologies
The higher the frequency, the lower the wavelength (e.g. for 77 GHz
RADAR or 60 GHz radio λ is few mm) and hence realizing an integrated
antenna becomes feasible
However lot of works still to do to achieve the high antenna gain
required by RADAR systems
2012 IEEE Radar Conference, May 7-11, Atlanta
Example of a single-package chip and
integrated antenna
Lots of on-chip antenna designs at 60 GHz for short-range consumer radio (the
antenna performance are less stringent than for typical RADAR systems)
Huei Wang , IEEE SIRF 2010
mm-Wave transceiver chip
with double-slot antenna
2012 IEEE Radar Conference, May 7-11, Atlanta
V-band transmitter and receiver with on-chip
(MMIC) integrated antennas
Huei Wang , IEEE Microwave Mag. 2009
2012 IEEE Radar Conference, May 7-11, Atlanta
Integrated antenna for RADAR systems
RADAR antennas are typically realized off-chip. Long-range Radar
automotive applications (100m-200m) require antennas with high gain
and high directivity which can not be realized on-chip (e.g. up to 20-25
dB in literature with a patch or horn or dish antenna)
For RADARs operating at frequencies below 10 GHz, the wavelength
amounts to several cm and hence it is not convenient to integrate the
antenna due to the high silicon area occupied
Single-chip antennas integrated on MMIC or SOI technology recently
proposed in literature for 60 GHz and 77 GHz (few dB gain) 
useful only for short-range applications and/or using special dielectric
lens antenna or smart resonator to improve the characteristics
2012 IEEE Radar Conference, May 7-11, Atlanta
Integrated antenna for RADAR systems
FMCW RADARs use separate TX and RX antennas
Pulsed RADARs can use the same antenna in time-division for TX/RX
By using an antenna array, a RADAR scanning effect can be obtained,
by realizing beam-forming in the analog domain (phase shifters) or in
the digital domain (digital beam-forming)
Unlike beam-forming, which presumes a high correlation between
signals either transmitted or received by an array, the Multiple-Input
Multiple-Output (MIMO) concept exploits the independence between
signals at the array elements to improve detection performance
In conventional single-antenna RADAR target scattering is regarded as
a parameter that degrades performance while MIMO RADAR takes the
opposite view capitalizing target scattering to improve performance
2012 IEEE Radar Conference, May 7-11, Atlanta
LTCC-integrated antenna example
LTCC-integrated example of CW-radar antenna +transceiver for near-field high
accuracy measures in industrial scenarios (C. Rusch et al., IEEE EuCAP’11)
2012 IEEE Radar Conference, May 7-11, Atlanta
Example of PCB-integrated antenna for
77 GHz automotive RADAR
Based on the FMCW principle, 4 77
GHz single microstrip patch antennas
combined with parasitic elements to
adjust bandwidth and beam-width
Antenna elements tilted by 45deg to
reduce interference from coming cars
The antenna elements serve as feeds
for a further dielectric lens resulting in
four narrow beams
RADAR sensor size of 7.4 x 7 x 5.8 cm3
(J. Hasch et al., IEEE Tran. Micr Theory Tech, 2012)
2012 IEEE Radar Conference, May 7-11, Atlanta
Example on-chip integrated antenna for
77 GHz automotive RADAR
On-chip antenna elements based on shorted λ/4 microstrip lines,
formed by the top and bottom metal layers of the chip backend
Most of the radiation dissipated due to conductor and dielectric losses,
resulting in a low antenna efficiency (<10%)
Quartz glass resonators are positioned above the on-chip patch
antenna elements to improve efficiency and bandwidth. The antennas
are spaced at a distance to allow direction of arrival (DOA) estimation
of a target or provide separate beams illuminating a dielectric lens
(J. Hasch et al., IEEE
Tran. Micr Theory Tech, 2012)
2012 IEEE Radar Conference, May 7-11, Atlanta
Performance of mm-Wave on-chip
integrated antenna
C. Person,
IEEE BCTM 2010
F
(GHz)
77
24
24
Tech
Gain
SiGe
GaAs
CMOS
60
Dipole
Slot Antenna
Cavity backed
folded dipole
Folded Dipole
Yagi
Spiral
60
Antenna type
4 array Dipole
Slot Dipole
Zig zag
Aperture
Coupled Patch
Feeder
Imped.
2
2
1.5
BW
(GHz)
2
1.4
N/A
Differential
CPW
N/A
45Ω
50 Ω
30 Ω
CMOS
7
7.8
Balanced
100 Ω
60
60
SiGe
CMOS
2.35
10
7
5
CPS
N/A
30 Ω
N/A
60
SiGe
7
18
CPS
50 Ω
60
60
SiGe
SiGe
CMOS
SOI
8
7
8
9.4
CPW
N/A
100 Ω
50 Ω
4.2
15
CPW
50 Ω
2012 IEEE Radar Conference, May 7-11, Atlanta
Semiconductor material properties
III-V high mobility devices (GaAs, InP, …) suited for high performance
at high frequencies (electrons rather hole carrier-based devices)
Devices (es. GaN) with wide energy-bandgap and breakdown voltage
suited for high voltage high power (e.g. vacuum tube replacement in
high transmitter power RADAR)
Si devices suited for large volume low-cost since dominate baseband
analog&digital processing for TLC, Computers, Consumer Electronics
2012 IEEE Radar Conference, May 7-11, Atlanta
FET vs. HBT basics
FET (Field Effect transistors) as MOS (Metal Oxide Semiconductor) or
HEMT (High Electron Mobility transistor) are unipolar devices (singlecarrier: electrons in HEMT and NMOS, holes in PMOS) while HBT is bipolar
(holes and electrons)
HBT and FET can act as digital (on/ff) or analog devices (current generator
controlled by an input current HBT or an input voltage FET)
HBT has an exponential drive characteristics while for FET is quadratic
HBT has higher transconductance (gain)
HBT has a resistive input impedance while for FET is capacitive  FET has
lower power consumption in standby mode
FET has lower noise at high freq (but it suffers of 1/f noise at low freq)
HBT are vertical integrated devices (high current density) while low-power
FET are planar devices (higher integration density and easier scaling)
2012 IEEE Radar Conference, May 7-11, Atlanta
Semiconductor technologies for RADAR
transceivers and ADC
In highly integrated low-power RADAR the vacuum-tube technologies
(Traveling Wave Tube, klystron, or magnetron,..) adopted for high power
high performance RADAR transmitter are completely avoided
Competing technologies are solid state ones:
- Monolithic microwave integrated circuits (MMIC) in compound III-V
semiconductors such as GaAs, In-P using High Electron Mobility FET
Transistors (HEMT)
- For power amplifier interest on GaN and SiC is increasing
- SiGe HBT (hetero-junction bipolar transistor) or BiCMOS (bipolarMOS) IC
- Si CMOS (N- and P- MOS) technologies IC
- CMOS SOI (Silicon on Insulator) IC
2012 IEEE Radar Conference, May 7-11, Atlanta
Competing technologies
2012 IEEE Radar Conference, May 7-11, Atlanta
Competing technologies
FT
Gain/NF
ratio
Cost
Power
Suited for
Consumption
BJT
High
High
Medium
High
Analog, RF
CMOS
Medium
Medium
Low
Low
Digital
BiCMOS
High
High
Medium
Medium
Analog, RF,
mixed-signal
HEMT
Very High
High
High
Medium
mm-wave
2012 IEEE Radar Conference, May 7-11, Atlanta
State of the art and trends in RADAR design
III-V MMIC
III-V MMIC (Monolithic Microwave Integrated Circuit) for radio/RADAR at
high frequencies developed since 70’s-80’s (dedicated US funding
programs for MMIC tech)
MMIC are now a mature technology, offering for analog circuitry (active
and passive components) at microwaves and mm-Waves best in class
performances (max Ft, NF and gain of LNA, gain and Psat of the PA)
MMIC dominates high-end transceivers from tens of GHz to THz
Most of MMIC are in GaAs technology (automotive RADAR front-end at
77/79 GHz, 60 GHz applications, 94 GHz imaging, Ka-, V-, W-Radar)
100-nm HEMT GaAs and 500-nm InP HBT tech. available
2012 IEEE Radar Conference, May 7-11, Atlanta
State of the art and trends in RADAR design
III-V MMIC
Limits of poor digital and mixed-signal integration capability  not
suited for low-cost, large volume, digital-based applications
Since 2005 III-V HEMT devices with Ft (the frequency at which the shortcircuit current gain is 1) of 700 GHz are available
Today we are going in the THz domain
However due to niche market applications, and higher device size, the
cost of ICs with III-V technologies is higher than that of silicon
technologies. While such cost is affordable in military or space
applications, for low-cost low-power civil RADAR applications silicon
technologies must be used
2012 IEEE Radar Conference, May 7-11, Atlanta
State of the art and trends in RADAR design
Si-based IC
Si-based technology dominates electronic industry for baseband signal
processing and IF (BB and IF circuitry integrated in the same SoC)
Since 2000 Si-based technologies (SiGe bipolar or CMOS) used for
telecom RF IC (cellular phone transceivers, WLAN, Bluetooth, UHF
wireless sensors)
Recent technology scaling proves the potential of CMOS, CMOS SOI or
BICMOS also for mm-Waves. Si-based mm-wave SoC developed in
recent years with commercial technologies for automotive RADAR (24
GHz and now 77/79 GHz) or TLC radio (60-GHz short-range)
Technologies: SiGe BiCMOS 130 nm, 180 nm; CMOS/CMOS SOI 130
nm, 90 nm, 65 nm, 45 nm, 32 nm, 28 nm; FDSOI at 28 nm and smaller
SiGe BiCMOS 130 nm, 180 nm or CMOS 90 nm, 65 nm used for RADAR
2012 IEEE Radar Conference, May 7-11, Atlanta
MOSFET, HBT and BiCMOS for RADAR design
In RADAR design HBT are more suited for high-frequency analog circuitry
ensuring higher gain and cut-off frequency, lower Noise Figure (NF)
MOSFET are more suited for the base-band DSP due to lower power
consumption, easier device scaling, higher integration levels, lower cost
SiGe BiCMOS (Bipolar Complementary MOS) allows the co-integration of
BJT for high-frequency applications and MOS devices for digital circuits
although at higher cost
At the state of the art the SiGe BiCMOS technology, with 130 nm
transistors channel length and an Ft of 230 GHz, offers a good trade-off
between cost and performance for single-chip mm-wave RADAR
transceivers. Several transceivers at 24, 77, 90, 120 GHz have been
proposed in literature using SiGe BiCMOS technology
2012 IEEE Radar Conference, May 7-11, Atlanta
MOS technology dominates DSP logic
M. Bhor, IEEE
ISSCC0’9
2012 IEEE Radar Conference, May 7-11, Atlanta
MOS technology dominates memory
2012 IEEE Radar Conference, May 7-11, Atlanta
Thanks to technology scaling
CMOS becomes suitable also for mm-waves
Huei Wang , IEEE SIRF 2010
For future, for large volume applications (60 GHz radio, RADAR?) the
trend will be using CMOS also for mm-wave circuits. As an effect of device
scaling a Ft higher than 150 GHz can be obtained
Realizing a mm-wave transceiver in scaled CMOS technology, as baseband
DSP, entails a lower area, higher integration and lower cost for large
volume markets but also lower performance vs. 130nm BiCMOS SiGe tech
2012 IEEE Radar Conference, May 7-11, Atlanta
Technology benchmark - oscillator
Oscillator phase noise (at 1 MHz from the carrier) vs. operating frequency
in mm-wave bands in various technologies
A. Scavennec et al.,
IEEE Microwave Mag. 2009
CMOS has comparable performance up to 70 GHz
2012 IEEE Radar Conference, May 7-11, Atlanta
Technology benchmark - oscillator
Oscillator output power (0 dBm=1 mW) vs. operating frequency in mmwave bands in various technologies
A. Scavennec et al.,
IEEE Microwave Mag. 2009
III-V devices have best in class performance, up to several hundreds of
GHz, CMOS realizable within 100 GHz but at lower performance
2012 IEEE Radar Conference, May 7-11, Atlanta
Technology benchmark – Power amplifier
A. Scavennec et al.,
IEEE Microwave Mag. 2009
On-chip mm-wave Power Amplifier is a big issue in CMOS
technology considering that from RADAR equation the range
capability heavily depends on transmitted power levels
2012 IEEE Radar Conference, May 7-11, Atlanta
Summary of GaAs vs. Si-based transceivers
2012 IEEE Radar Conference, May 7-11, Atlanta
SiGe – processes from different vendors
Most offers bipolars and FET and passive components
(J. Hasch et al., IEEE
Tran. Micr Theory Tech, 2012)
2012 IEEE Radar Conference, May 7-11, Atlanta
SiGe – Ft vs. Ic
(J. Hasch et al., IEEE
Tran. Micr Theory Tech, 2012)
Technology evolution allows for higher ft at a given current or the same ft
for lower current: this reduces power consumption, power supply and
thermal issues reducing size and cost and increasing reliability in harsh
environments
2012 IEEE Radar Conference, May 7-11, Atlanta
SiGe – Power Amplifier capability
2012 IEEE Radar Conference, May 7-11, Atlanta
SiGe vs. CMOS vs. III-V technologies
For applications at mm-Wave bands lower NF expected for SiGe and CMOS
hence the same performance available with lower transmit power and hence
small size and lower costs
Source: International technology Roadmap for semiconductors (ITRS)
2012 IEEE Radar Conference, May 7-11, Atlanta
CMOS capability- LNA (Gain)
Gain, dB - CMOS LNA
25
20
15
10
1
F (GHz)
10
100
State-of-art designs up to 10-20 GHz in CMOS technology have good
performances: gain higher than 20 dB
At higher frequencies the performances start decreasing.
Around 77 GHz (W-band) acceptable but non optimal performance are
achieved today (gain lower than 20 dB)
2012 IEEE Radar Conference, May 7-11, Atlanta
CMOS capability- LNA (NF)
NF, dB - CMOS LNA
10
8
6
4
2
0
1
F (GHz)
10
100
State-of-art designs up to 10-20 GHz in CMOS technology have optimal
performances: NF lower than 4 dB
At higher frequencies the performances start decreasing
Around 77 GHz (W band) acceptable but non optimal performance are
achieved today (NF higher than 4 dB)
2012 IEEE Radar Conference, May 7-11, Atlanta
CMOS capability- PA
Pout TX, dBm - CMOS PA
At frequencies of few GHz an integrated PA up to 1 W peak power is possible
The peak power of integrated PA decreases with frequency
At high frequency (77 GHz or higher, W band ) the peak power is < 10 dBm (10 mW)
Only short range applications are possible with high duty cycle or external off-chip
PA are needed
35
30
25
20
15
10
5
0
1
10
F (GHz)
100
1000
2012 IEEE Radar Conference, May 7-11, Atlanta
Issues in Si-based transceivers
Another issue in Si-based transceivers is the design of low-losses passive
components such as CoPlanar Stripline or Waveguides (CPS/CPW)
At mm-Wave frequencies, due to very short wavelength, the antenna
integration is possible but low efficiency and low gain are main concerns
Solution migration to SOI technologies
2012 IEEE Radar Conference, May 7-11, Atlanta
CPW, CPS and Antenna In CMOS SOI
In SOI technology the high resistivity of the substrate on which n- and pMOSFET are created allows dielectric isolation of circuit elements
Junction capacitances are reduced increasing maximum operating freq
Reduced noise coupling between digital-analog parts integrated in the
same chip
The performances of CPS, CPW or antennas in SOI CMOS are improved
due to a reduced amount of energy loss in the supporting substrate
2012 IEEE Radar Conference, May 7-11, Atlanta
Integrated antenna in CMOS SOI
Incidence of substrate resistivity on achievable radiation efficiency and gain
(bulk 20 Ω/cm, SOI > 1000 Ω/cm)
F. Gianesello,
IEEE SOI 2010
2012 IEEE Radar Conference, May 7-11, Atlanta
Quality factors of inductance in CMOS SOI
F. Gianesello, IEEE SOI 2010
2012 IEEE Radar Conference, May 7-11, Atlanta
CMOS SOI useful also for high speed digital
applications vs. bulk CMOS
P. Simonen, IEEE IMC 2001
2012 IEEE Radar Conference, May 7-11, Atlanta
Antenna in CMOS SOI
Single-chip integrated antennas on 65 nm CMOS SOI recently proposed in
literature: a double-slot antenna with CPW feed, tunable to operate in
different mm-wave frequencies has been proposed with a gain of 4.4 dB (at
60 GHz) and an area occupation of 1 mm2
2012 IEEE Radar Conference, May 7-11, Atlanta
Antenna in CMOS SOI
2012 IEEE Radar Conference, May 7-11, Atlanta
ADC – main cost figures
The ADC is gaining a key role in RADAR systems due to trend of digitization
of the signal processing functionalities
Main cost figures of interest are:
Bits (Effective number of bits –ENOB- rather than nominal bits)
Sampling frequency, Number of channels
Integral and Differential Non Linearity (INL, DNL)
Signal-to-Noise and Distortion Ratio (SNDR)
Spurious Free Dynamic Range (SFDR)
Aperture uncertainty
Area, power consumption
2012 IEEE Radar Conference, May 7-11, Atlanta
ADC – RADAR requirements
RADAR architectures may require ADC operating at intermediate frequency
and not only at base band frequency: sampling rates up to tens, or even
hundreds, of MS/s can be required in highly digitized RADAR
The number of ADC channels depends on the system architecture (1 or 2
for I-Q for each of the K RADAR channels, e.g. 4 in last LRR automotive
Bosch RADAR)
The bit resolution is typically higher than 10 b, e.g. a nominal 14b -16 b
required for 12 b-14 b ENOB (at least 70 dB dynamic range)
Specs on non linearity and aperture uncertainty ta depends, together with
ENOB bits N, also on the required SNR level
2012 IEEE Radar Conference, May 7-11, Atlanta
Comparing performance of different
architecture types
L . Bin et al., IEEE Signal Proc. Mag., 2005
Absolute data not updated (see
next slide) but useful relative
architecture comparison
2012 IEEE Radar Conference, May 7-11, Atlanta
ADC – Performance available (2011)
M. Mishali et al. IEEE Signal Proc. Mag. 2011
2012 IEEE Radar Conference, May 7-11, Atlanta
ADC – Conclusions
ADC sampling at several GS/s available but too-high power
consumption per channel and too low bit resolution for typical
RADAR dynamic range and SNR requirements  Mixer is needed,
full-digital RADAR is not convenient
IF ADC can reach the required bit resolution and sampling rate with
good power performance (e.g. 100 MS/s, 16-b nominal at least 14
ENOB) with power consumption within hundreds of mW
Pipelines or time-interleaved SAR can be suited architectures
Figure of Merit (FoM) in scaled CMOS technologies can be in the
range fJ to pJ per conversion-step
2012 IEEE Radar Conference, May 7-11, Atlanta
RADAR Technologies – Recent Bibliography
J. Hasch et al., Millimeter-Wave Technology for Automotive Radar Sensors in the 77 GHz
Frequency Band, IEEE Tran. Micr. Theory and Tech, 2012
T. Mitomo et al., A 77 GHz 90 nm CMOS transceiver for FMCW radar applications, IEEE J. SolidState Circuits 2010
Y.-A. Li et al., A fully integrated 77 GHz FMCW radar transciever in 65 nm CMOS, technology,
IEEE J. Solid-State Circuits 2010
W. Menxel et al., Antenna Concepts for Millimeter-Wave Automotive Radar Sensors,
Proceedings of the IEEE, 2012
V. Giammello et al., A Transformer-Coupling Current-Reuse SiGe HBT Power Amplifier for 77GHz Automotive Radar, accepted on IEEE Tran. Micr. Theory and Tech.
B. Neri, S. Saponara, Advances in Technologies, Architectures and Applications of HighlyIntegrated Low-power Radars, IEEE Aerospace Electr. Syt. Mag. 2012
B. Brannon et al., Analog devices AN-501,Aperture Uncertainty and ADC System Performance
M. Mishali et al., Sub-nyquist sampling, IEEE Signal Proc. Mag. 2011
L . Bin, et al., Analog-to-digital converters, IEEE Signal Proc. Mag., 2005
P. Harpe et al., A 7-to-10b 0-to-4MS/s Flexible SAR ADC with 6.5-to-16fJ/conversion-step, IEEE
ISSCC 2012
Bei Yu et al, A 14-bit 200-MS/s Time-Interleaved ADC with Sample-Time Error Detection and
Cancelation, IEEE ASSCC 2011
Y. M. Greshishchev, A 40GS/s 6b ADC in 65nm CMOS, IEEE ISSCC 2010
2012 IEEE Radar Conference, May 7-11, Atlanta
RADAR Technologies – Recent Bibliography
D. Liu et al., Integration of Array Antennas in Chip Package for 60-GHz Radios, Proceedings of
IEEE 2012
F. Gianesello, SOI CMOS Technology for Wireless Applications: Current Trends and Perspectives,
IEEE Int. SOI conf. 2010
C. Person, Antennas on Silicon for millimeter-wave applications – status and trends, IEEE BCTM
2010
A. Scavennec et al., Semiconductor technologies for higher frequencies, IEEE Microwave
Mag. 2009
Huei Wang, Current status and future trends for Si and Compound MMICs in millimeter wave
regime and related issues for System on Chip (SoC) and System in Package (SiP), IEEE SIRF 2010
M. Bhor, The New Era of Scaling in an SoC World, IEEE ISSCC 2009
S. Saponara , B. Neri et al, Feasibility study and on-chip antenna for fully integrated μRFID
tag at 60 GHz in 65 nm CMOS SOI, IEEE RFID-TA 2011
S. Saponara, B. Neri et al, Integrated 60 GHz Antenna, LNA and Fast ADC Architecture for
Embedded Systems with Wireless Gbit Connectivity, Journal Circuit Systems Computers 2012
Huei Wang et al., MMICs in the millimiter-wave regime, IEEE Microwave Mag. 2009
P. Simonen, Comparison of bulk and SOI CMOS technologies in a DSP processor circuit
implementation, IEEE ICM 2001
C. Rusch et al., W-Band Vivaldi Antenna in LTCC for CW Radar Near field Distance Measurements,
IEEE EuCAP 2011
2012 IEEE Radar Conference, May 7-11, Atlanta
Outline of the tutorial
Scenarios and applications for highly-integrated
low-power RADAR
RADAR architecture and analog-digital
partitioning
RF/mm-Wave RADAR transceivers and ADC
Ubiquitous low-power RADAR case studies:
vital sign detection, automotive driver assistance
Digital signal processing for RADAR
HW-SW implementing platforms for RADAR
digital signal processing
Conclusions
2012 IEEE Radar Conference, May 7-11, Atlanta
Ubiquitous low-power RADAR
architecture case studies
Why a RADAR as contactless health sensor?
UWB pulsed bio RADAR
Doppler bio RADAR
Why a RADAR for automotive driver assistance?
Standards, frequency and technology selection
Automotive RADAR spec and commercial devices
FMCW RADAR architecture
SiGe automotive RADAR
CMOS automotive RADAR
2012 IEEE Radar Conference, May 7-11, Atlanta
Needs for health monitoring
Due to aging population and needs of national health system cost
reduction there is high interest in monitoring electronic health devices,
specially for heart or respiratory pathologies (CHF, BPCO)
A low-cost RADAR can be used as contactless sensor for monitoring
heart rate or breath rate in patient with cardiopulmonary illness or to
monitors babies while sleeping against sudden infant death syndrome
Acquired RADAR data are then processed by an home gateway an
send to Hospital Information Server
2012 IEEE Radar Conference, May 7-11, Atlanta
Why RADAR for vital signs sensing
A RADAR can sense the mechanical activity of heart of chest instead
of the electrical one and from that the heart or breath rate can be
detected and estimated
The RADAR bio sensor can ensure continuous home monitoring
avoiding wires, gels, LOS requirement, electrodes of conventional
solutions based on SpO2 measures and multi-lead ECG acquisition
(prone to electrode error positioning when done outside hospital )
Sensor RADAR requirements are low-power and high miniaturization
for portability/wearability, short-range, low cost for large volume
market  CMOS silicon integrated approach should be followed
No ionizing effect
2012 IEEE Radar Conference, May 7-11, Atlanta
Which RADAR architecture?
Recent proposals based on Ultra Wide Band pulsed RADAR (within
3-10 GHz range) for very low power and low complex short-range
(tens of cm) contactless vital sign detection
Correlator-type receiver (Zito, De Rossi, Neri, architecture 20072010, implementation in 90 nm CMOS 2011-2012), (Ta-Shun Chu et
al., 130 nm CMOS implementation in 2011)
Doppler RADAR based on transmission of un-modulated signal and
the analysis of the received echo phase modulated by the
chest/heart movement (Dracourt 2004, several works by J. Li, J. Lin
et al.). Various designs at 450 MHz, 1.6 GHz, 2.4 GHz, 5.8 GHz in
various technologies (250 nm CMOS and BiCMOS, 130 nm CMOS,..)
2012 IEEE Radar Conference, May 7-11, Atlanta
UWB pulsed RADAR
Very low power spectral density (-41.3 dBm/MHz from 3.1 to 10 GHz,
14 bands each of 500 MHz) – ETSI/FCC regulation
Robust against interference
No ionization effect
Transceiver activated only when needed (low power consumption due
to low duty cycling)
2012 IEEE Radar Conference, May 7-11, Atlanta
UWB pulsed RADAR
Due to low power the RADAR is limited to detection of heart/breath
rate of few Hz, at distances of tens of cm
Single TX/RX antenna multiplexed in time
Transmitter: pulse generator in the TX path transmits short pulses,
typically 200-400 ps, towards the human body with a pulse repetition
frequency (fPR) > 1 MHz so that the heart can be considered motionless between consecutive pulses. The energy level of each pulse
amounts to few pJ
Zito et al., IEEE TBCS, 2011
2012 IEEE Radar Conference, May 7-11, Atlanta
UWB pulsed RADAR
Low-complex cross correlation receiver architecture (differential path to
improve EMI robustness)
The output signal is modulated by the heart movement, acting as a target
with a cross sections of tens of cm2
After a TOF dependant on the target distance (e.g. few ns for 15-30 cm
distance) the signals reflected by the target is captured by the RX antenna
RADAR works in ranging mode (delay varied to span the range of interest
and identify the target) or tracking mode (once detected, the delay is fixed
for target tracking)
Vo (t) at multiplier output
Vout (t) at integrator output
2012 IEEE Radar Conference, May 7-11, Atlanta
Receiver-type correlation
The signal amplified by the LNA is multiplied with a delayed replica of
the transmitted pulses generated on-chip by a Shaper circuit
The amplitude of the signal at the output of the multiplier is related to
the heart position. Since vital signs vary within a few Hertz, an
integrator 3-dB band (Bint) of 100Hz allows an accurate detection.
Averaging a large number of pulses allows us to increase the SNR (e.g.
the SNR improvement is 40 dB with Bint=100 Hz and fPR=1 MHz)
SNRimp
f PR
 10  log(
)
Bint
2012 IEEE Radar Conference, May 7-11, Atlanta
Flicker noise issue at receiver
At the low frequency (DC-100 Hz) of the baseband bio-signal the MOS
transistors used for RADAR-on-chip integration suffer 1/f flicker noise,
much higher than thermal noise (KTB term)
The total NF of a multi-stage RX path is
NFtot  NF1  ( NF2 1) / G1  ( NF3 1) / G2G1
To have NFtot~NFLNA a gain of at least 20 dB is required for the LNA stage
provided that NF2<10-15 dB, a value feasible at state of the art
LNA realized in 90 nm CMOS with 22.7 db gain (3-stage), 6 dB NF, -19
dBm ICP1,<35 mW, <0.7 mm2 area
Fully differential Gilbert cell mixer in 90 nm CMOS with NF 14.3 dB, 12 dB
Gain, 3.7 mW, 0.3 mm2 area
The integrator realized with a 3-stage gm-c cell (cut-off 145 Hz, 1 mW)
2012 IEEE Radar Conference, May 7-11, Atlanta
Transmitter
Pulse generator based on triangular pulse generation (TPG) and shaping
network (SN): two triangular pulsed (delayed by a pulse period) generated
and shaped by a CMOS differential pair
2012 IEEE Radar Conference, May 7-11, Atlanta
Performance of state of art UWB RADARs
fPR in the range 1-10 MHz, pulses of 300-400 ps and 7-8 pJ energy
The baseband digital processing can be realized with a simple MCU
since low-speed ADC is required (12bit ADC in ISSCC’11), low data rate
serial connection, only control tasks to be implemented
Whole chip by Zito et al. in 90 nm CMOS has <2 mm2 area, < 80 mW
power consumption, 40dB SNR integrator improvement, <1m range
RADAR packaged in QFN32 and mounted on a test-board including
antennas (TX and RX) with 2.3 dBi gain at 3.5 GHz, band 2.8 to 5.4 GHz
covering the range of interest from 3 to 5 GHz.
Whole chip by Ta-Shun Chu et al. in 130 nm CMOS has <12 mm2 area,
<700 mW power consumption, 34.7 dB SNR integrator improvement,
<15 m range
2012 IEEE Radar Conference, May 7-11, Atlanta
Doppler Bio RADAR
In DR for noncontact vital sign detection an un-modulated signal is
transmitted towards the human body, where it is phase modulated by
the physiological movement, then reflected and captured by the
radar receiver (h and r are heart and respiratory rate respectively)
C. Li et al., IEEE TIM 2010
2012 IEEE Radar Conference, May 7-11, Atlanta
Doppler Bio RADAR
Using the same un-modulated TX signal as the RX LO signal, the
receiver down-converts the received signal into baseband with no
frequency offset. Here it is digitized and the physiological movement
(i.e., heartbeat and respiration) can be identified by DSP (FFT or
wavelet proposed in literature)
C. Li et al., IEEE Tran. Micr. Theory Tech. 2010
2012 IEEE Radar Conference, May 7-11, Atlanta
Doppler Bio RADAR
A doppler RADAR with 5.8 GHz central frequency and 1 GHz
bandwidth has been realized in 130 nm CMOS technology powered
by 1.5V batteries and using direct conversion quadrature architecture
The LNA has 2.56 dB NF and 24 dB gain
The system is sized to ensure 10-20 dB SNR, using a baseband
sampling rate of 20 Hz (ADC is sized for 1 kHz)
The whole RX chain has min 37 dB gain, -32 dBm P1dB
sensitivity of -101 dBm
and a
Off-chip 2x2 patch antennas (separate for TX and RX) were used
With 7 dBm output power detection up to 3 m can be done
The received power is from -37 dBm to -61 dBm when the target
distance increases from 50 cm to 2 m
2012 IEEE Radar Conference, May 7-11, Atlanta
Vital Signs Detection RADAR – Bibliography
D. Dracourt et al., Range Correlation and I/Q Performance Benefits in Single-Chip Silicon Doppler
Radars for Noncontact Cardiopulmonary Monitoring, IEEE Tran. Micr. Theory Tech 2004
D. Zito et al., SoC CMOS UWB pulse radar sensor for contactless respiratory rate monitoring, IEEE
Tran. Biomedical Circuits and Systems 2011
C. Li et al., Accurate doppler radar noncontact vital sign detection using the RELAX algorithm, IEEE
Tran. Instr. and Measur. 2010
C. Li et al., Radar Remote Monitoring of Vital Signs, IEEE Microwave Mag. 2009
D. Zito et al., A 90nm CMOS SoC UWB pulse radar for respiratory rate monitoring, IEEE ISSCC’11
Ta Shun Chu et al., A short-range UWB impulse-radio CMOS sensor for human feature detection,
IEEE ISSCC’11
G. Reyes et al., VitalTrack: a doppler radar sensor platform for monitoring activity levels, IEEE
BioWireleSS 2012
M. Mercuri et al, SFCW microwave radar for in-door fall detection, IEEE BioWireleSS 2012
Tariq et al., Vital signs detection using Doppler radar and continuous wavelet transform, IEEE
EuCAP 2011
A. Lazaro et al., Vital signs monitoring using Impulse Based UWB Signal, IEEE EuMA 2011
G. Blumrosen et al., Noncontact tremor characterization using low-power wideband radar
technology, IEEE Tran. Biomedical Eng. 20120
C. Li et al., High-Sensitivity Software-Configurable 5.8-GHz Radar Sensor Receiver Chip in 0.13um
CMOS for Noncontact Vital Sign Detection, IEEE Tran. Micr. Theory Tech 2010
C. GU et al., Instrument-based noncontact doppler radar vital sign detection system using
heterodyne digital quadrature demodulation architecture,
IEEE
Tran.Conference,
Instr. and Measur.
2010
2012 IEEE
Radar
May 7-11,
Atlanta
Automotive RADAR – Why?
Automotive RADARs as core sensor (range, speed) of driver assistance
systems: long range (LRR) for Adaptive Cruise Control, medium range
(MRR) for cross traffic alert and lane change assist, short-range (SRR)
for parking aid, obstacle/pedestrian detection
W.r.t. to other sensing technologies RADAR is robust in harsh
environments (bad light, bad weather, extreme temperatures)
Multiple RADAR channels required for additional angular information
Data fusion in the digital domain with other on-board sensors
2012 IEEE Radar Conference, May 7-11, Atlanta
Automotive RADAR –a bit of Story
First tentative for mm-wave automotive RADAR since 70’s (but
integrated-unfriendly technologies lead to large size, high cost)
Since 1998-1999 first generation of RADAR sensors (Daimler, Toyota)
Since 2000 MMIC GaAs-based RADAR in premium cars
Last generation based on 180/130 nm SiGe chipset and advanced
packaging with integrated antenna commercially available (e.g. Bosch)
Radar CMOS transceivers recent announced in 65 nm and 90 nm
High RADAR frequency (small λ) allows small size and weight; highly
integration with SiGe and future CMOS tech. will reduce assembly and
testing costs and hence final user cost much below US$1000
Market expanding at 40%/year and is expected increasing with all
premium/middle cars having a RADAR in next years (7% of all vehicles
sold world-wide, mainly in Europe, Japan and US, will have RADARs)
2012 IEEE Radar Conference, May 7-11, Atlanta
Automotive RADAR – Regulation
24 GHz and 77 GHz are the dominant bands for automotive
77-81 GHz is promising since offers 4 GHz bandwidth
2012 IEEE Radar Conference, May 7-11, Atlanta
Automotive RADAR – 24 vs. 77 GHz
77 GHz is more challenging for designers: given the same technology
the node performances (gain, NF, ..) at 24 GHz are better but 77 GHz
RADARs reduce size, volume, weight and hence cost
77 GHz offers more opportunity for high performance RADAR design:
λ is 3 times smaller (few mm)  smaller antenna size for a given beamwidth spec and/or better angular separability for the same size
Combination of high transmit power and high bandwidth available at 77
GHz for long range operation and fine distance separability
Due to SiGe and CMOS technologies evolution 77 GHz is affordable
77-81 GHz (under regulation worldwide) offers 4 GHz Bandwidth with
EIRP max PSD of - 3dBm/MHz (-9 dBm/MHz outside the vehicle)
2012 IEEE Radar Conference, May 7-11, Atlanta
Automotive RADAR – Technical spec
(J. Hasch et al., IEEE
Tran. Micr Theory Tech, 2012)
2012 IEEE Radar Conference, May 7-11, Atlanta
Automotive commercial RADARs
(J. Hasch et al., IEEE
Tran. Micr Theory Tech, 2012)
Product size is in the order of 7 cm per side in LRR, 5 cm per side or lower
in MRR and SRR
Products exist with mechanical (slowly, increased size) or electronic beam
forming (increased electronic complexity affordable in new tech nodes)
Multi channel transceivers required
All use FMCW RADAR technique
2012 IEEE Radar Conference, May 7-11, Atlanta
FMCW Automotive RADAR principle
f
Target
VCO
Quartz
Osc
fref
Phase
det.
t
Loop
filter
PA
R
Freq. divider
Interface
User I/O
77 GHz
TOF=2R/c
LO
Modulation
control (B, Tm)
X
LNA
RF
f TX
RX
DSP
FFT &
logic
ADC
amp
f fbeat
fbeat

t
TOF
t
Received signal at the ADC
2012 IEEE Radar Conference, May 7-11, Atlanta
FMCW Automotive RADAR equations
Receiver power and SNR (min 10 dB required)
Pt Gt Gr 2
Pr 
(4 ) 3 R 4
fd 
2  vr

Pr
SNR 
K  T  NF  BWFFT
cTcpi ( f   f  )
R

2B
2
c ( f   f )
vR 

2  fc
2
Range and relative speed detection from batiment frequency analysis
(with FFT in digital domain)
The FMCW sweep frequency B and the time sweep determine the
achievable range resolution and speed resolution
2012 IEEE Radar Conference, May 7-11, Atlanta
Automotive RADAR – Technology Selection
Automotive RADAR based on GaAs MMIC in production, multiple chips
and boards needed thus increasing assembly and testing cost
Last generation based on SiGe chipset (HBT or BiCMOS): less ICs thus
reducing cost, already mature technology for 77 GHz, 2 boards (1 for
radar transceiver and 1 for RADAR baseband processing)
W.r.t CMOS SiGe today offers higher fmax, up to 200-300 GHz (at least
20% reduction is expected at extreme temperatures), higher output
power (Psat of 15-16 dBm available) and is mature for mass production
CMOS transceivers in 90 nm and 65 nm for 77 GHz already published,
some improvements needed for automotive mass production but CMOS
has high integrating potential (transceivers and baseband DSP)
Today SiGe-based RADAR, tomorrow CMOS-based RADAR expected
given technology evolution and trends towards more digital RADAR
2012 IEEE Radar Conference, May 7-11, Atlanta
Automotive RADAR with SiGe mm-Wave T/R
Commercially available from Bosch
based on SiGe Infineon Chipset
2 PCB boards
FCMW modulation
LRR 7dBm Pout, 4 channels (2 TX/RX,
2 RX only), dielectric lens antenna
provides high gain for Rmax 250m
Alternative versions with PCB or onchip Integrated antennas
B. Fleming, IEEE Vehicular Tech. Mag. 2012
2012 IEEE Radar Conference, May 7-11, Atlanta
Block diagrams of automotive RADAR with
SiGe mm-Wave T/R
(J. Hasch et al., IEEE
Tran. Micr Theory Tech, 2012)
2012 IEEE Radar Conference, May 7-11, Atlanta
Performance of transceivers in CMOS
technology
JSSC2010
JSSC2010
IEEEAESM 2012
65 nm
CMOS
90nm
CMOS
guidelines
243 mW
517 mw
N/A
1 mm2
6.8 mm2
N/A
77 GHz
77 GHz
77 GHz
Resolution
N/A
<
Doppler resolution
N/A
~5 km/h
Range and
antenna gain
with
off-chip 24 dB
antenna
8m with
off-chip 20 dB
antenna
>100m with off-chip 24
dB antenna,
<10 m with on-chip 4 dB
antenna
On-chip PA output
5 dBm
-2.8 dBm
<10 dBm
Technology
Power
consumption
Area
Carrier frequency
RX gain
LNA+mixer+IF
Sweep time Tm
1.5 ms
23 dB
LNA+mixer
0.5 ms
Sweep freq. B
700 MHz
614 MHz
FFT points
2048, 3 MS/s
4096, 2 MS/s
~38.7 dB
~40 dB
~1 ms
150-750 MHz
up to 8192, few MS/s
2012 IEEE Radar Conference, May 7-11, Atlanta
Automotive RADAR – Recent Bibliography
J. Hasch et al., Millimeter-Wave Technology for Automotive Radar Sensors in the 77 GHz
Frequency Band, IEEE Tran. Micr Theory and Tech, 2012
T. Mitomo et al., A 77 GHz 90 nm CMOS transceiver for FMCW radar applications, IEEE J. SolidState Circuits 2010
Y. Kawano et al., A 77 GHz transceiver in 90 nm CMOS,” IEEE ISSCC 2009
Y.-A. Li et al., A fully integrated 77 GHz FMCW radar transciever in 65 nm CMOS, technology,
IEEE J. Solid-State Circuits 2010
R. Stevenson, A driver’s sixth sense, IEEE Spectrum 2011
S. Trotta et al., An RCP Packaged Transceiver Chipset fo Automotive LRR and SRR Systems in
SiGe BiCMOS Technology, IEEE Tran. Micr- theory and tech, 2012
B. Fleming, Recent Advancement in Automotive Radar Systems, IEEE Vehicular Tech. Mag. 2012
W. Menxel et al., Antenna Concepts for Millimeter-Wave Automotive Radar Sensors,
Proceedings of the IEEE, 2012
V. Giammello et al., “A Transformer-Coupling Current-Reuse SiGe HBT Power Amplifier for 77GHz Automotive Radar”, accepted on IEEE Tran. Micr Theory and Tech
B. Neri, S. Saponara, Advances in Technologies, Architectures and Applications of HighlyIntegrated Low-power Radars, IEEE Aerosp. Eelectr. Syst. Mag. 2012
2012 IEEE Radar Conference, May 7-11, Atlanta
Outline of the tutorial
Scenarios and applications for highly-integrated
low-power RADAR
RADAR architecture and analog-digital
partitioning
RF/mm-Wave RADAR transceivers and ADC
Ubiquitous low-power RADAR case studies:
vital sign detection, automotive driver assistance
Digital signal processing for RADAR
HW-SW implementing platforms for RADAR
digital signal processing
Conclusions
2012 IEEE Radar Conference, May 7-11, Atlanta
Main signal processing functions in
classical RADARs:
Digital range compression
Single and multi beamforming
Space-time adaptive processing
CFAR techniques
Direction of arrival (DOA) estimation
Tracking
2012 IEEE Radar Conference, May 7-11, Atlanta
Digital pulse compression
Frequency of phase modulated long signals are transmitted and
compressed in reception for improving range resolution.
The receiver is a matched filter/correlator. The correlation can be done in
time or frequency domain. The most common is the frequency domain
through FFT. Many pulses are then integrated for target detection.
2012 IEEE Radar Conference, May 7-11, Atlanta
Digital pulse compression
The FFT/IFFT is the core of the digital pulse compression
8-point, Radix-2 FFT
2012 IEEE Radar Conference, May 7-11, Atlanta
Digital pulse compression
2012 IEEE Radar Conference, May 7-11, Atlanta
Single and multi beamforming
To form a beam in a particular direction, each element of the array needs
to be followed by a time delay such that when all the outputs are summed
they add up coherently to form a beam
Analog beamforming
Figures from Skolnik book
Digital beamforming
2012 IEEE Radar Conference, May 7-11, Atlanta
Single and multi beamforming
Analog beamforming used to implement subarrays, followed by digital
receivers and digital phase shifter. In digital domain, the beamfomers are
FIR filters with complex weigths
Analog/digital beamforming
Figure from Skolnik book
2012 IEEE Radar Conference, May 7-11, Atlanta
Space-Time Adaptive Processing
STAP is an advanced signal processing technique used in airborne RADAR
applications to suppress interferences by performing jointly data-adaptive
beamforming (space domain) and Doppler processing (time domain)
2012 IEEE Radar Conference, May 7-11, Atlanta
Space-Time Adaptive Processing
R. Klemm, J. Ward, STAP tutorial, 2008
2012 IEEE Radar Conference, May 7-11, Atlanta
STAP: data cube
R. Klemm, J. Ward, STAP tutorial, 2008
2012 IEEE Radar Conference, May 7-11, Atlanta
Optimum STAP
R. Klemm, J. Ward, STAP tutorial, 2008
2012 IEEE Radar Conference, May 7-11, Atlanta
Optimum STAP
The core of the STAP is the inversion of the disturbance covariance matrix,
adaptively estimated both in time and space domains using secondary
vectors.
Direct computation of the weight vector w by inverting Rˆ is not practical
for STAP due to the huge dimension of Rˆ itself. Generally the STAP system
try to solve the equivalent linear system
ˆ  kv
Rw
through the QR decomposition after covariance matrix estimation.
The number of RFLOPs with QR decomposition is of order of (NM)3.
QR decomposition can be applied directly to secondary vectors avoiding
the matrix estimation. With L secondary vectors the number of RFLOPs is
8 L  MN   2.67  MN 
2
3
2012 IEEE Radar Conference, May 7-11, Atlanta
Reduced dimension STAP
R. Klemm, J. Ward, STAP tutorial, 2008
2012 IEEE Radar Conference, May 7-11, Atlanta
Incoherent CFAR detector
(only amplitude information is used)
2012 IEEE Radar Conference, May 7-11, Atlanta
Incoherent CFAR detectors
Depending on the adaptive threshold Z we have different CFAR techniques
CA-CFAR : Z=mean(X1, X2,…. XN)
GO-CFAR: Z1=mean(X1, X2,…. XN/2)
Z2=mean(XN/2+1, XN/2+2,…. XN)
Z=max(Z1, Z2)
SO-CFAR: Z1=mean(X1, X2,…. XN/2)
Z2=mean(XN/2+1, XN/2+2,…. XN)
Z=min(Z1, Z2)
OS-CFAR: Y=sort(X1, X2,…. XN)
Z=YK
2012 IEEE Radar Conference, May 7-11, Atlanta
Coherent adaptive CFAR detectors
(both I and Q components are used)
For Gaussian target in Gaussian clutter we have:
 AMF (z ) :
2
ˆ 1z H1
v R
> 
H ˆ 1
v R v <
H0
H
target steering vector
complex envelop of the observed signal
2
ˆ 1z H1
v R
>   (z H R
ˆ 1z )
ˆ 1 v <
vH R
H0
H
 ANMF (z ) :
 GLRT (z ) :
2
ˆ 1z H1
v R
>   1  1 z H R
ˆ 1z 


ˆ 1 v ) <
K
(vH R


H0
H
clutter covariance matrix
estimated by secondary
vectors
2012 IEEE Radar Conference, May 7-11, Atlanta
DOA estimation - Monopulse
It needs two beams for each angular coordinate
Sum and difference patterns are used
It can use single or multiple pulses
H. Rohling, Automotive Radar tutorial, 2008
2012 IEEE Radar Conference, May 7-11, Atlanta
DOA estimation - Monopulse
Normalized antenna pattern
1
0.5
Example, with Gaussian
antenna pattern and
-3dB beamwidth=3o
0
-0.5


-1
-8
-6
-4
-2
0
2
4
6
8
azimuth  (degrees)
Ideally, without noise
2012 IEEE Radar Conference, May 7-11, Atlanta
Tracking - Linear Kalman filter
Kk  P  P  R 
*
k
Object parameters
Measurement
Sensor
 t xk 
 
t
y k   yk 
 vxk 
 
 v yk 
 t xk 
 
t yk 

yk 
 vxk 
 
 v yk 
Linear model
 t xk

 t yk

 vxk
v
 yk
 1
 
 0
  0
 
 0

H. Rohling, Automotive Radar tutorial, 2008
0 T
1
0
0
0
1
0
*
k
Linear
Kalman
Filter
1
Track estimate
Prediction
 t xk* 
 * 
t yk 

yk  *
 vxk 
 * 
 v yk 
0   t xk 1 



T  t yk 1 

0   vxk 1 


1  v 
 yk 1 
 tˆxk 
ˆ 
t yk 

yˆ k 
 vˆxk 
 
 vˆ yk 
y k  Ay k 1
2012 IEEE Radar Conference, May 7-11, Atlanta
Linear Kalman filter
Prediction step:
- Prediction estimation based on Process matrix A:
yˆ *k  Ayˆ k 1
- Track estimation:
Pk*  APk1AT  Q
Track estimation step
- Prediction accuracy estimation based on tracking accuracy and process noise:
yˆ k  yˆ k*  K k  yk  yˆ k* 
- Tracking accuracy estimation:
Pk   I  K k  P
*
k
Kalman gain based prediction
accuracy and measurement noise
Kk  P  P  R 
*
k
*
k
1
2012 IEEE Radar Conference, May 7-11, Atlanta
Some
applications
2012 IEEE Radar Conference, May 7-11, Atlanta
Automotive RADARs
Functionalities:
•Autonomous cruise control (ACC)
•ACC support with Stop&Go functionality
•Pre-crash sensing
•Collision mitigation and avoidance
•Parking aid (forward and reverse)
•Lane change assistant
•Rear crash collision warning
Goals:
Simultaneous measurement of obstacle range,
radial velocity and angle
2012 IEEE Radar Conference, May 7-11, Atlanta
Long Range RADAR (LRR)
Observation area
Requirements for LRR RADAR
Functionalities: Autonomous Cruise Control (ACC)
Collision warning
2012 IEEE Radar Conference, May 7-11, Atlanta
LRR for vehicular applications
Transmitted signals
Some special waveforms must be used to fulfill the requirements of
simultaneous range and radial velocity measurement:
•Pulse Doppler
•FMCW with (at least) up- and down-chirp signals
•Frequency Shift Keying (FSK) CW
•MFSK CW
2012 IEEE Radar Conference, May 7-11, Atlanta
LRR for vehicular applications
Single channel scheme
 
Bsw t 2  
sT (t )  cos  2  fT t 

TCPI 2  
 
sR (t )  sT t   t 
2B
2
f B ,1  f D  f   vr  sw R

cTCPI
2B
2
f B ,2  f D  f   vr  sw R

cTCPI
Parameters for an LRR radars
24 GHz or 77 GHz
H. Rohling, Automotive Radar tutorial, 2008
2012 IEEE Radar Conference, May 7-11, Atlanta
LRR for vehicular applications
FFT: applied on each segment (up and down chirp)
frequency and range estimation accuracy depends on the number of FFT
points. Typical values: 128-4096 points
up chirp
H. Rohling, Automotive Radar tutorial, 2008
down chirp
f B ,1
f
B ,2
2012 IEEE
Radar Conference, May 7-11, Atlanta
LRR for vehicular applications
With only one up and down chirp , two targets are ambiguous. With
four chirps two targets can be easily resolved
H. Rohling, Automotive Radar tutorial, 2008
2012 IEEE Radar Conference, May 7-11, Atlanta
LRR for vehicular applications
CFAR techniques for detection
Most common: 1D-CA-CFAR applied on
FFT output (frequency domain)
Signal processing
DOA estimation
Most common: Monopulse
with two antennas
Tracking techniques after detection
Most common: linear KF
2012 IEEE Radar Conference, May 7-11, Atlanta
UWB RADARs
Chacteristics:
Low power consumption
Low cost circuitry
Low probability of detection
Different materials and environments distort pulses differently
Applications:
Vehicular RADAR (Short range)
Ground Penetrating RADAR (GPR)
Trough-the-wall imaging
Medical RADARs
2012 IEEE Radar Conference, May 7-11, Atlanta
UWB RADAR definition
The amount of spectrum occupied by a signal transmitted by a UWB-RADAR (i.e.
the bandwidth of the UWB signal) is at least 25% of the center frequency. Thus, a
UWB signal centered at 2 GHz would have a minimum bandwidth of 500 MHz
and the minimum bandwidth of a UWB signal centered at 4 GHz would be
1 GHz. Often the absolute bandwidth is bigger than 1 GHz.
narrowband
UWB
noise
2012 IEEE Radar Conference, May 7-11, Atlanta
UWB RADAR for medical applications
D
S
P
D
S
P
static signal cancellation
How does it work?
FFT and frequency estimation
2012 IEEE Radar Conference, May 7-11, Atlanta
UWB RADAR for medical applications
2012 IEEE Radar Conference, May 7-11, Atlanta
UWB RADAR for medical applications
Frequency band: 3.1 -10.6 GHz, typical bandwidth: 2 GHz
2012 IEEE Radar Conference, May 7-11, Atlanta
UWB RADAR for medical applications
Chest movements for breathing and heart beat: the time delay of the
reference signal in the correlator is fixed to the position of the target, then
any movement will change the output amplitude at the receiver.
The relationship between the target distance and the output amplitude is
almost linear around the correlation maximum, then a distance change can
be directly seen through the amplitude of the output signal
Measured sensor output for a
breathing person and a breath hold of
about 12 s
Transmitted pulse: 1st derivative
Gaussian pulse
Distance fixed to the skin-air boundary
Heart beat
2012 IEEE Radar Conference, May 7-11, Atlanta
UWB RADAR for medical applications
static signal cancellation
Xs=mean(X)
Y=X-Xs
FFT and frequency estimation
• Undesired harmonic terms and
intermodulations other than the
sinusoids of interest
• The third and forth- order harmonics
of respiration signal are very close to
the
frequency
of heart
beat,
complicating the output spectrum
• Need for frequency super-resolution
methods (like RELAX or MUSIC)
2012 IEEE Radar Conference, May 7-11, Atlanta
UWB RADAR for medical applications
Predicted attenuation of pulse-echo traveling from the transmitting antenna
to the receiving antenna. Each step accounts for echo at the boundary.
Decreasing of the curve accounts for linear attenuation in the tissue
RCS of the heart @5GHz: 0.001 m2
2012 IEEE Radar Conference, May 7-11, Atlanta
Doppler Bio RADAR
How does it work?
C. Li et al., IEEE TIM 2010
•The transmitter generates a CW signal
•The phase shift of the reflected signal is proportional to the time-varying
chest position
•Spectral analysis through FFT or super-resolution method estimate beat and
breath frequencies
2012 IEEE Radar Conference, May 7-11, Atlanta
Conclusions
Automotive applications: in the future a network of small
RADARs will be used to improve the performance in terms
of angular, frequency and range accuracy and in terms of
number of tracked targets
Biomedical applications: use of MIMO RADAR techniques
to mitigate the noise caused by other body motion artifacts
2012 IEEE Radar Conference, May 7-11, Atlanta
References
M. A. Richards, “Fundamentals of Radar Signal Processing,” McGraw-Hill, 2005, ISBN 0-07-144474-2.
S. Lal, R. Muscedere, S. Chowdhury, “An FPGA-Based Signal Processing System for a 77 GHz MEMS Tri-Mode
Automotive Radar,” 2011 22nd IEEE International Symposium on Rapid System Prototyping, 2011 , pp. 2 - 8.
S. Venkatesh, C.R. Anderson, N.V. Rivera, R.M. Buehrer, "Implementation and analysis of respiration-rate estimation
using impulse-based UWB", IEEE MILCOM 2005, 2005, pp. 3314-3320, Vol. 5
M. Leib, W. Menzel, B. Schleicher, H. Schumacher, " Vital signs monitoring with a UWB radar based on a correlation
receiver", Fourth European Conference on Antennas and Propagation (EuCAP), 2010, pp. 1 - 5
H. Dominik "Short Range Radar - Status of UWB Sensors and their Applications", 4th European Radar Conference,
2007, pp. 251-254.
J. J. Alter, J.O. Coleman, “Radar Digital Signal Processing", Ch. 25 in Introduction to Radar Systems, ed M. Skolnik”,
McGraw Hill.
R.H. Hosking, "FPGA Cores Enhance Radar Pulse Compression", COTS Journal, October 2003, pp. 32-35.
H. Rohling, "Radar Sensors for Automotive Applications", tutorial 2008 IEEE Radar Conference, Rome
R. Klemm, J. Ward, "Space-Time Adaptive Processing Architectures and Algorithms", tutorial 2008 IEEE Radar
Conference, Rome
2012 IEEE Radar Conference, May 7-11, Atlanta
Outline of the tutorial
Scenarios and applications for highly-integrated
low-power RADAR
RADAR architecture and analog-digital
partitioning
RF/mm-Wave RADAR transceivers and ADC
Ubiquitous low-power RADAR case studies:
vital sign detection, automotive driver assistance
Digital signal processing for RADAR
HW-SW implementing platforms for RADAR
digital signal processing
Conclusions
2012 IEEE Radar Conference, May 7-11, Atlanta
HW-SW implementing platforms for
RADAR digital signal processing
Overview of implementing platforms for RADAR
DSP
Custom SoC (System-on-Chip)
MCU (Microcontroller Unit)
GPP (General Purpose Processor)
DSP (Digital Signal Processor) and GPU (Graphics
Processing Unit)
High-end FPGA (Field Programmable Gate Array)
Cost-effective FPGA
2012 IEEE Radar Conference, May 7-11, Atlanta
Implementing platforms for RADAR DSP
Ubiquitous integrated RADAR applications (automotive, bio,..) needs lowpower consumption (reduced power supply and thermal issues and
increased portability) but can require high computational capabilities and
large data transfer rate and memory storage size
Energy-flexibility trade-off to be found between
Software-oriented platforms (GPP, DSP, GPU, Microcontroller)
and Hardware-oriented platforms (custom IC-SoC or MPSoC, FPGA)
Note: apart custom SoC designs or microcontrollers, external ADC and
DAC are required since only digital interfaces are provided
2012 IEEE Radar Conference, May 7-11, Atlanta
Implementing platforms for RADAR DSP
Main performance metrics to be considered:
- Computational capabilities: GOPS (Giga Operations Per Second) and if
there are DSP-dedicated instructions (e.g. Multiply, MAC, …)
- Operand bit-width and arithmetic type (Fixed, Floating or Block Floating
Point Operations)
- Memory: access frequency, size and hierarchy levels
- Flexibility: level of re-programmability or re-configurability
- Efficiency (GOPS/MHz, GOPS/mW, GOPS/mm2)
- On-chip available I/O interfaces (type, data-rate, supported protocols …)
2012 IEEE Radar Conference, May 7-11, Atlanta
Custom SoC design for RADAR DSP
Custom SoC design can provide the best in terms of performance for a
given technology at minimum area and power occupation
Digital and mixed (ADC, DAC) functions can be integrated together in
CMOS, flexibility can be achieved integrating in the ASIC also
programmable cores
Development time and costs are high (cost is minimized only for large
volume productions)
Today, RADAR system concept for bio, automotive or other ubiquitous
applications is still changing from one platform generation to the next
Automotive RADAR is not yet a commodity application with accepted and
frozen standards
2012 IEEE Radar Conference, May 7-11, Atlanta
Architecture for cost-effective RADAR DSP
Rather than designing custom SoC for RADAR in next years an
architecture based on MCU+ (DSP or FPGA) is considered more suited
Thanks to the availability of IP cores such designs can be seen also a
prototyping step towards a migration to SoC if and when RADAR will
become a commodity
R. Whil, IWPC 2011
2012 IEEE Radar Conference, May 7-11, Atlanta
Microcontroller Unit (MCU)
MCU are typically characterized by low-cost low-power but lowperformance capabilities (MIPS rather than GOPS, integer operations,
low data–rate digital I/O), ADC/DAC can be integrated on-chip
MCU are the core of ubiquitous electronic systems (automotive ECUs)
For RADAR, MCU are suitable only for applications needing control of
data/operation flow but not DSP (e.g. the digital controller of the UWB
pulsed RADAR health detector with analog correlator and integrator)
In automotive RADARs the MCU acts as a baseband control unit and
manages the telemetry/telecontrol on vehicle network (CAN or FlexRay
bus) but a DSP or FPGA co-processor is required if computing intensive
signal processing is needed (pulse compression, filtering, FFT, CFAR,…)
2012 IEEE Radar Conference, May 7-11, Atlanta
Why not General Purpose Processors (GPP)?
GPP are evolving as SW-programmable computing architecture with
many cores, large operand size (64b or higher), tens of GOPS, multiple
cache levels (several Mbytes on chip) and fast connections to off-chip
DDR memories or networks
However the energy efficiency (<<1GFLOPS/Watt) and absolute power
(tens of Watts) are far from specs of highly-integrated low-power RADAR
applications
Intel I5 multicore example
2012 IEEE Radar Conference, May 7-11, Atlanta
Digital Signal Processors
SW-programmable processors with instruction set optimized for DSP (e.g.
ALU as HW resources for fast MAC implementations) rather than general
purpose computing
Fixed or floating point versions available
Different architectural approaches: SIMD, VLIW up to GPU
High-end computing performance (GPU) of TFLOPS higher than multicore GPP and with better energy efficiency for DSP tasks
DSP for consumer, automotive and biomedical markets already available
DSP available also as IP cores (soft or hard macrocells) to be integrated in
custom IC
Vector SIMD DSP (Synergistic Processor of CELL BE) and GPU analyzed
and compared
2012 IEEE Radar Conference, May 7-11, Atlanta
Graphics Processing Unit (GPU)
GPUs are evolving as massively parallel platforms for graphics but also
for computing-intensive algorithms with high degree of parallelism
Fermi NVIDIA GPU composed of 512 CUDA (Compute Unified Device
Architecture) processing cores hierarchically organized in 16 streaming
multi-processors each with 64-kB L1 cache, 128-kB local register file,
and sharing 768-kB L2 cache. 4 MB total on-chip memory
The Fermi GPU has PCIe host interface and six 64-b DDR DRAM
interfaces. Each CUDA core is capable of integer and floating point
operations with 64-b results. Each of the 16 streaming processors has
also 4 40-b units for fast approximation of non linear operators
(square root, sin, cos, exp, log functions) and 16 load/store units.
The Fermi GPU leads to a computational power up to 1500 GFLOPS in
single-precision, 1 order of magnitude higher than GPP
2012 IEEE Radar Conference, May 7-11, Atlanta
GPU for RADAR signal processing
Real time RADAR DSP processing is not an issue for such GPUs
GPU’s area and power costs (and power supply and thermal issues) are
not suited for highly integrated low-power RADAR applications
GTX480 Fermi NVIDIA, realized in 45 nm CMOS, has a transistor count
of 3 billions, a core area of 422 mm2 and the power consumption > 150
W when implementing algorithms with a workload > 500 GFLOPs
The NVIDIA Quadro 4000 GPU has 256 CUDA cores, 4 64-b DDR DRAM
interface and a max. power consumption of 100 W
2012 IEEE Radar Conference, May 7-11, Atlanta
GPU vs GPP
Comparison of computational and bandwidth capabilities and power cost
of some GPP and GPUs
2012 IEEE Radar Conference, May 7-11, Atlanta
GPU vs GPP
NVIDIA GTX260 GPU tested against Core2Duo GPP E8x series for several
RADAR DSP classic algorithms:
e.g. FFT and IFFT, Timed domain FIR (TDFIR), Frequency domain FIR
(FDFIR, consisting of FFT + TDFIR + IFFT), Single value decomposition
and QR-decomposition on complex large size matrix, CFAR, matrix rowcolumn transposition, bi-cubic interpolation, STAP using covariance
matrix, STAP using QRD
GPU has a speed-up from 10% up to two orders of magnitude vs. GPP
depending on:
the algorithms, the size of the input array data, the regularity and
parallelization degree of the data flow, the bottleneck caused by
memory transfers (the GPU kernel can be faster than the whole GPU
computing platform considering also the memory system)
2012 IEEE Radar Conference, May 7-11, Atlanta
GPU vs GPP: speed up for TDFIR
For TDFIR the GPU kernel has a speed-up up to 80x vs. GPP, considering also
memory transfer the speed-up is reduced, the higher the length of the
input array data the higher the GPU speed-up
Patterson et
SAAB 2010
al,
2012 IEEE Radar Conference, May 7-11, Atlanta
GPU vs GPP: speed up for CFAR
For CFAR the GPU kernel has a speed-from 3x to 30X but considering
also memory transfer the speed-up is reduced to x 1.1 for small data set
Patterson et al, SAAB 2010
2012 IEEE Radar Conference, May 7-11, Atlanta
GPU vs GPP: speed up for FFT
Kernel GPU
Patterson et al, SAAB 2010
Total GPU speed up: kernel +memory system
2012 IEEE Radar Conference, May 7-11, Atlanta
Vector DSP – Synergistic Processor of CELL
Vector processor
128 bit SIMD (Single Instruction Multiple Data)
128 registers each 128 bits wide
25.6 GFLOPS (single precision), 51 GOPS (8 bit)
Two- to sixteen-way SIMD
Memory control
Load/store instructions can
access only local store
256KB local store
SP includes DMA instructions
for explicitly moving data
between local store
and main memory
2012 IEEE Radar Conference, May 7-11, Atlanta
The CELL BE multi-core DSP
• Cell BE processor integrates 9 processors on a single die
– 1 Power® processor + 8 vector SP processors
• Computational Performance
– 205 GFLOPS @ 3.2 GHz, 410 GOPS @ 3.2 GHZ
• High-speed communication ring  205 GB/s maximum sustained bandwidth
• High performance chip interfaces  25.6 GB/s XDR main memory bandwidth
2012 IEEE Radar Conference, May 7-11, Atlanta
CELL BE vs. GPP: FFT and 2D FIR benchmarks
60
56
Cell BE 3.2 GHz
Freescale 744x 975 MHz
50
Pentium 3.6 GHz 2MB L2
Relative Performance
Opteron 2.4 GHz
40
PPC 970 2.0 GHz
32
30
30
25
20
13
10
1.8
1.0 1.5 0.9
1.0
2.1
1.3
2.0
1.0
1.9
1.0 1.0
1.0
1.0
0
1K point FFT
8K point FFT
64K point FFT
15x15 16-bit filter
15x15 8-bit filter
Patterson et al, SAAB 2011
2012 IEEE Radar Conference, May 7-11, Atlanta
Trendline of DSP- and GPP-oriented platforms
Die size, number of transistors, computational power (GOPS) and power
consumption of single core systems (ATOM 230 and 1 SP- Cell BE), and
multi core systems (ATOM330, Fermi GPU GTX480, Core2, Cell BE, Tile64)
2012 IEEE Radar Conference, May 7-11, Atlanta
FPGA (Field Programmable Gate array)
FPGAs are evolving from reconfigurable HW devices to complex Systems
on Programmable Chip (SoPC) with: integrated reconfigurable logic
blocks (based on FF, LUT) and I/O blocks, memory blocks, DSPdedicated units (Multiply, Acc), soft or hard cores (Microblaze, Nios,
ARM Cortex,..) for SW-programmability and HW- reconfigurability
Different FPGA technologies exist: Flash (ProAsic), Anti-fuse (AX, RTAX) ,
SRAM (Virtex, Spartan, Cyclone, Stratix) some already qualified for
automotive or even space/military applications
For DSP intensive applications SRAM-based are typically preferred
Mixed-signal FPGAs also exist(Fusion)
FPGA designs for DSP require algorithmic
and HW know-how (HDL and synthesis tools)
2012 IEEE Radar Conference, May 7-11, Atlanta
High-end FPGA for RADAR DSP
High-end FPGAs for intensive RADAR DSP are available but their cost
(>1000 USD) and power consumption are too high for ubiquitous lowpower applications (rather suited for defense, avionic or marine radars)
E. Chung, IEEE/ACM Micro 2010
Virtex6 LX760 FPGA device in 40
nm for FFT processing has 380
GFLOPS at a power cost of 50 W
LX760 FPGA has worse efficiency,
(GFLOPS/W, GFLOPS/mm2), by 1
order of magnitude vs. custom IC,
better performance by 1 order of
magnitude vs. GPP and slightly
better than GPU (GTX480)
2012 IEEE Radar Conference, May 7-11, Atlanta
High-end FPGA for RADAR DSP
Stratix Altera FPGA in 28 nm with variable precision DSP blocks (Mul
18x18, 27x27,18x36 etc., 64 bit acc) with 2000 GMACs
Several RADAR DSP functions implemented such as STAP, digital beamforming, pulse compression
Altera 2012
However to fit the DSP RADAR requirements of low-cost low-power
applications the challenge is an optimized algorithmic-architecture codesign on less complex FPGA families with HW-SW capabilities
2012 IEEE Radar Conference, May 7-11, Atlanta
Cost-effective FPGA for RADAR DSP
MCU+DSP functionalities of a FMCW automotive RADAR realized in
Xilinx Virtex2Pro (Microblaze + radix-2 FFT processor 2048-point, 14 b)
Control and DSP functionalities of a 77 GHz FMCW RADAR with GaAs
MMIC front-end and MEMS switch realized in Spartan-3A and Virtex-5
SX50T which manage switch control, TX sweep generation, Hamming
filtering, FFT (radix-2 2048-point), CA-CFAR, peak pairing
11b ADC, 10b DAC, 12b/16b DSP data/coefficient resolution
S. Lal, IEEE RSP 2011
2012 IEEE Radar Conference, May 7-11, Atlanta
Cost-effective FPGA for RADAR DSP
Virtex5 SX50T: 8160 slices (4 LUT+4FF), 5000 kb RAM; 288 DSP48 unit
(25x18 mul+acc +adder), 12 DCM 6 PLL, fast I/O
Spartan3 A-DSP (XA3SD1800A): 16640 slices (2LUT+2FF), 1500 kb RAM,
84 18x18 mul, 8 DCM, automotive grade device exist
S. Lal, IEEE RSP 2011
2012 IEEE Radar Conference, May 7-11, Atlanta
Cost-effective FPGA for RADAR DSP
From first simulation results the Virtex-5 RADAR version is more
performing and has comparable performance to LRR3 RADAR
S. Lal, IEEE RSP 2011
2012 IEEE Radar Conference, May 7-11, Atlanta
Implementing platforms for RADAR DSP–
Recent Bibliography
J. Pettersson et al., Radar signal processing with GPU, SAAB doc. 5/0363-FCP1041180 en, p.
127, 2010
E. Chung et al., 2010, Single-Chip Heterogeneous Computing: Does the Future Include Custom
Logic, FPGAs, and GPGPUs?, IEEE/ACM 43rd Micro 2010
R. Whil, Fast growing, diversified Automotive Radar Market presents chip vendors with new
challenges , IWPC 2011
S. Lal, An FPGA-based signal processing system for a 77 GHz MEMS tri-mode automotive radar
, IEEE RSP 2011
V. Mauer, et al., Floating point STAP implementation on FPGAs , IEEE Radar conf. 2011
J. Saad, FPGA-based Radar Signal Processing for Automotive Driver Assistance System, IEEE Int.
Symp, Rapid prot. 2009
S. Lal et al., An FPGA-based 77 GHZ MEMS radar signal processing system for automotive
collision avoidance; IEEE CECE 2011
Altera, White Paper Using Floating-Point FPGAs for DSP in Radar, May 2011
S. Saponara et al., A multi-processor NoC-based architecture for real-time image/video
enhancement, JRTIP 2012
2012 IEEE Radar Conference, May 7-11, Atlanta
Conclusions
RADAR sensing is suited to address societal needs of safety, security,
health-care, intelligent transport with big advantages vs. other
technologies
Differently from high power and large antenna RADARs, highlyintegrated systems with low power consumption, size, and cost are
needed for the ubiquitous adoption of RADARs in large–volume markets
At mm-waves (λ of few mm) there are great opportunities for
miniaturization
Key enabling factor is the realization, in Si-based CMOS or BiCMOS
tech., of integrated transceivers for the RADAR front-end with enough NF,
gain and Power to meet automotive or bio RADAR requirements
2012 IEEE Radar Conference, May 7-11, Atlanta
Conclusions
The ADC is moving at IF offering enough bit-resolution and samplingrate at low energy cost per conversion step
Increasing RADAR signal processing in the digital domain (FFT, filtering,
pulse compression, beam-forming, CFAR, tracking), realized in costeffective embedded platforms (MCU+FPGA), allows for high performance
RADAR in standard technologies at low power consumption and low size
Proof-of-concept demonstrators of this scenario and first commercial
solutions recently available for UWB Pulsed RADAR for vital signs
detection and FMCW RADAR for automotive LRR, MRR and SRR
The path to full CMOS/CMOS SOI to be completed as well as advanced
concepts for System-in-Package integration to be further explored
2012 IEEE Radar Conference, May 7-11, Atlanta
Conclusions
Automotive applications: in the future a network of small RADARs
will be used to improve the performance in terms of angular, frequency
and range accuracy and in terms of number of tracked targets
Biomedical applications: use of MIMO RADAR techniques to mitigate
the noise caused by other body motion artifacts
Data fusion of low-power ubiquitous RADAR systems with other
sensor technologies (e.g. camera)
In networked RADAR sensor scenario new DSP functions to be
adopted (e.g. code division multiple access to avoid crowding)
2012 IEEE Radar Conference, May 7-11, Atlanta
Thanks for your attention
Acknowledgment
Discussions with
Bruno Neri, Full Professor of RF electronics
and
Fulvio Gini, Full Professor of Telecommunications
at University of Pisa
are gratefully acknowledged
2012 IEEE Radar Conference, May 7-11, Atlanta
Brief Biographies of the Speakers
Sergio Saponara graduated in Electronic Engineering cum laude and received the Ph.D. degree in
Information Engineering from the University of Pisa. In 2002 he was with IMEC, Belgium, as Marie Curie
Research Fellow. Since 2001 he collaborates with Consorzio Pisa Ricerche (I) to technology transfer projects
in the field of integrated systems. Currently, he is Professor of Electronics at University of Pisa in the field of
microelectronics and electronic systems, including integrated wireless systems. He co-authored more than
160 scientific publications and 10 patents and is Associate Editor of the Journal of Real-Time Image
Processing, Springer. He has also associations with the Italian National Institute for Nuclear Physics (INFN)
and with the Italian interuniversity consortium for telecommunications (CNIT). He served as special issue
guest editor on international journals and as committee member or session chairman for international
conferences such as IEEE Euromicro DSD 2008, IEEE DATE from 2006 to 2012, IEEE MTT-S IMWS 2011, IEEE
ISIEA 2012
Maria S. Greco graduated in Electronic Engineering in 1993 and received the Ph.D. degree in
Telecommunication Engineering in 1998, from University of Pisa. From December 1997 to May 1998 she
joined the Georgia Tech Research Institute, Atlanta, USA as a visiting research scholar where she carried on
research activity in the field of radar detection in non-Gaussian background. Currently she is Associate
Professor of Telecommunications at University of Pisa. She is IEEE Fellow and she was co-recipient of the
2001 IEEE Aerospace and Electronic Systems Society's Barry Carlton Award for Best Paper. She has been cogeneral-chair of the 2007 International Waveform Diversity and Design Conference (WDD07), and she was
in the technical committee of EUSIPCO 2006. She is guest co-editor of the special section of the Journal of
the IEEE Signal Processing Society on Special Topics in Signal Processing on "Adaptive Waveform Design for
Agile Sensing and Communication“ 2007. She has given lectures at universities and institutions in Italy and
abroad. Her general interests are in the areas of statistical signal processing, estimation and detection
theory. Her research interests include cyclostationarity signal analysis, DOA estimation techniques, clutter
models, spectral analysis, coherent and incoherent detection in non-Gaussian clutter and CFAR techniques
2012 IEEE Radar Conference, May 7-11, Atlanta