UWB Short Range (Radar) SensorsUWB Short Range...
Transcript of UWB Short Range (Radar) SensorsUWB Short Range...
UWB Short Range (Radar) SensorsUWB Short Range (Radar) SensorsUWB Short Range (Radar) SensorsUWB Short Range (Radar) Sensors
Reiner S. Thomä
IlmenauUniversity of Technology
Slide 1Technische Universität Ilmenau FG Elektronische Meßtechnik
WCI 2008
UWB – An Idea Whose Time Has Come?UWB – An Idea Whose Time Has Come?
Communication – Localization – Sensors
Communication:• “New frequencies” for short range communication q g
FCC 2002: 3.1 - 10.6 GHzBack to Marconi?
• Coexistence with other systems • Simple systems and hardware
Localization:• Unprecedented delay resolution (bandwidth!) • Multipath resistance
Sensors:• Material penetration (low frequencies!)• More information on materials and shape of scanned media and bodies
Slide 2Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
UWB Spectrum Regulation - FCC
-30
z]-40
m/M
Hz
critical gapfor sensor
applications
-60
-50
vel [
dBm
EIRP = -41,3 dBm/MHzR l f fi ld
0,5 mW- 3 dBm
-70
-60
RP
lev
indoor applications
Rms value of field strength of 500 µV/m measured GPS
band
-80
EI
hand held devices, outdoorpp
1 10
at 3 m distance and 1 MHz bandwidth
frequency [GHz]EIRP = effective isotropic radiated power
Slide 3Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
Basic UWB System ConsiderationsBasic UWB System Considerations
• Impulse radio, OFDM or direct sequence spread spectrum?
• Integrated system design example – Experimental system as used for all examples given
• Basic localization principles • Radar imaging
Slide 4Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
System Characterization in the Time Domain
Impulse excitation:
( ) ( ) ( ) ( )ttxthty δ~if~
Excitation: reaction IRFExcitation:Impulse
reaction ~ IRF
LTI-Systemh(t)h(t)x(t) y(t)
Slide 5Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
Correlation Processing
Excitation: noise
reaction
(t)LTI-System
h(t)x(t)
y(t) l t
h(t)yy(t) correlator
cyx(τ)x
Cross-correlation ~ IRF
Slide 6Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
Maximum Length Binary Sequence (MLBS)
S
Ideal 4th order M-Sequenceone period
ctNT =0V M
S
time
one chip tc = 1/fc
N = 2n-1Number of chips:Time-Bandwidth-Product: nTB 2≈Auto correlation function Time Bandwidth Product: TB 2≈
1
Auto correlation function
CorrelationCorrelationGain!10 lg(TB)
Slide 7Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
0
Single Chip Demonstrator System in SiGeSingle Chip Demonstrator System in SiGe
RF-clock to DSPADCVee = 3 V
Rx
TTx Rx
ADCli l k
Courtesy M. Kmec,TU Ilmenau
Slide 8Technische Universität Ilmenau FG Elektronische Meßtechnik
2008 8to DSPSampling clockTrigger
Experimental System (Baseband)Experimental System (Baseband)
Transmit signal spectrum (not calibrated)
Direct wave
C t lkDirect wave
Cross-talkSystem impulse response Noise floor
IR, not calibrated IR calibrated
Slide 9Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
35dB dynamic range 60dB dynamic range
Demonstrator System 3.5…10.5 GHzDemonstrator System 3.5…10.5 GHz
Digitalhift i t
Modulated MLBS
RF-clockshift register
to sensor
7 GHz
MLBS
Binarydivider
Complex ImpulseResponse Function
00 9001/2LO unit
Sampling Clock13.6 MHz
HDigital signalprocessingIRF ADC
T&H
from sensor
IF – Front - EndBase Band Processing
Slide 10Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
Basic Radar Signal Processing Basic Radar Signal Processing
TxPort 1
Tx
reference
Targeta1
b2Rx
2
Port 2IRF h(t)
• Radar echo depends on target size shape and materialsize, shape, and material composition• desired target information: ( )t permittivity
gdistance, location, orientation, speed, shape, material
iti iti
( )τεε ,,,, tzyx=
( )τμμ ,,,, tzyx=
ε permittivityμ permeabilityσ conductivityx,y,z space coordinatest observation time
Slide 11Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
composition, recognition… ( )τσσ ,,,, tzyx=t observation timeτ delay time
Spatial Processing and Radar Imaging Spatial Processing and Radar Imaging
Measured data
Focused data
Measured data
ObjectCross range single scan
contribution
Time delay Focused dataTime delay
Measured data
Slide 12Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
UWB Localization and Sensor ApplicationsUWB Localization and Sensor Applications
•Localization of active devices (tags) •Localization and recognition of passive objectsLocalization and recognition of passive objects •Imaging of structures and environments•Material characterization
•Non destructive testing•Civil engineering and miningSh t i ti•Short range navigation
•Industrial sensing•Safety and security•Automotive •Biomedical engineering•Law enforcement, military, y•Search and rescue
Slide 13Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
Humanitarian Demining (GPR)
3 x 3 UWB array and metal detector
9 channel M-Sequence UWB Radar
Courtesy QinetiQ
Courtesy MEODAT and QinetiQ
Slide 14Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
Humanitarian Demining (GPR)
APL and UXO Detection
“Wave penetration” into the soil
APL
R2M2 -Mine
APL3
cm
Courtesy Vrije Universiteit Brussels
Ground surface profile gained by the radar
(Demonstrating video)
Slide 15Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
gained by the radar
Non-Destructive Testing in Civil Engineering
Experimental Set-up
Arrangement of 5 by 3 bricks
Slide 16Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
Non-Destructive Testing in Civil Engineering
Detection of wall structures, artefacts, moisture
antenna polarisation
yyall bricks are dry
y
xx
y
the central brick was exposed to watery
Slide 17Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
xx
Radar Sewer Tube CrawlerRadar Sewer Tube Crawler
Antenna unit
• radar unit• operation controlp• angle sensor• data interface
Test field in preparation with foreign objects
Slide 18Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
g j
Radar Sewer Tube Crawler: Measurement exampleRadar Sewer Tube Crawler: Measurement example
Slide 19Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
Detection of human body activities: cardiac & respiratoryDetection of human body activities: cardiac & respiratory
heart beat rate: 83
Measurement data withMeasurement data with background subtraction breathing stop breathing
Slide 20Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
MRI Image EnhancementMRI Image Enhancement
Tracking of heart and lunge movement
Slide 21Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
Cancer DetectionCancer Detection
Variation of water content Variation of water content b hi hb hi h
In vitro measurement of a human lung during by approaching the cancerby approaching the cancer
8888
a human lung during NaCl-Perfusion
8282848486868888
onte
nt [%
]on
tent
[%]
787880808282
Wat
wer
co
Wat
wer
co
7676
Slide 22Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
Active Location ApproachActive Location Approach
Measured Example • cm (sub-cm) precision
2
2.5
t l t k
measured trackdetected wave front
circular wave front
R l t
1.5
tion
[m] actual track
time [ns]
Real antenna
?0.5
1
Y di
rect ϕ = 90°
45°
?
1 0 5 0 0 5 1
0
ϕ = - 45°
ϕ = 0°
ϕ = 45°
-1 -0.5 0 0.5 1
X direction [m]receive array
moved transmit antenna
Slide 23Technische Universität Ilmenau FG Elektronische Meßtechnik
2008 23
(Vivaldi antennas)transmit antenna
(bi-cone)
Active Location ApproachActive Location ApproachMeasured example: 3D-positioning
sandbox
Demonstrating video
Vivaldi-Array
Slide 24Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
Passive ApproachPassive ApproachExample
2
2.5moving target(box 0,5 x 0,1 x 0,5 m)
1.5
2tio
n [m
]
0 5
1
Y di
rect actual track
measured track
0
0.5 measured track
-1 -0.5 0 0.5 1
X direction [m] receive array(Vivaldi antennas)
transmit antenna(bi cone)
Slide 25Technische Universität Ilmenau FG Elektronische Meßtechnik
2008 25
(Vivaldi antennas)(bi-cone)
Search and Rescue Applications Search and Rescue Applications
Detection of people buried by an avalanche
Detection of people buried by earthquake
Tracking of peoplebehind the wall
Rescue personnel, injured persons in static environments
Recognition of building structures• hidden rooms and cavities
• detection respiratory activity• detection cardiac activity• moving persons
• wall structures• blocked entrance
Slide 26Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
g
Tx/Rx node
y[m] [x3,y3]
Tx node
[0,0]
[xm100,ym100] Rx node
[ , ]
[xm1,ym1]
[x2,0]
x[m]
Slide 27Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
Imaging of Environments: Measured ExampleImaging of Environments: Measured Example
• Rx1 and Rx 2: anchor nodes
• Tx: roaming illuminator node
• Direct and scattered wave separated
• Tx position track estimated from direct wave
• Image of environment calculated from scattered waveImage of environment calculated from scattered wave
Measurement environment
Container
Measurement environment
Data measured by anchor node
Rx1
Direct wave
Rx1 Rx2
Tx moving
Engine 2
Engine 1 Wall Multipath components
Slide 28Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
Imaging of Environments: Measured ExampleImaging of Environments: Measured Example
Engine 2Rx1 contribution to the focused image
Container
Rx1
Tx
the focused image - single snapshot
Engine 1Focused image from Rx1 and Rx2 contribution
Container Estimated track of
Rx1 Rx2
Tx moving
Engine 2 the Tx movement
Engine 1 Wall
Slide 29Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
g
Imaging by “Bat-type” Sensors Imaging by “Bat-type” Sensors
2T
xR
x2R
x1
„Bat-type“ sensors are equipped with one Tx and two Rx antennas
Object 1
Object 2
R
No coherent cooperation of distributed sensors required
Sensor positioning maybe self j p g ycontained
Additional positioning (inertial sensors or by anchor nodes) may help
Tx Rx2Rx1Resulting image
y ) y p
Correlation of single snapshots
Object 1Object 2
snapshots
Slide 30Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
Object 2
Imaging of Objects: ResolutionImaging of Objects: Resolution
Slide 31Technische Universität Ilmenau FG Elektronische Meßtechnik
200824
Localizing of people – through the wallLocalizing of people – through the wall
1st part of
Measurement scenario
500cm
1st part of the track
2nd part of the track
500cm
Table
3rd part of the track
4th part of Table the track
Test object
30cmWooden door
Furniture
Slide 32Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
Rx1 Tx1 Rx2 Tx2 Rx3 Tx3200cm 200cm
Localizing of people – through the wallLocalizing of people – through the wall
Antenna arrangement
Demonstrating video
Slide 33Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
Measurement scenario in reality
Through Wall Detection of Breathing ActivityThrough Wall Detection of Breathing Activity
Tx antenna Rx antennaTx antenna Rx antenna
40cm
Wooden door
200cm
5 times deep breath
Brick wall
5 times deep breath slow
5 times deep breath fast4 times flat breathing
Test object
Slide 34Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
Test object
Detection of buried people
Detection of Breathing and heart beatDetection of Breathing and heart beat
e, n
s 20
22e, n
s 20
22e, n
s 20
22
Radar data after removing static scatterer
gatio
n Ti
me 22
24
26
gatio
n Ti
me 22
24
26
gatio
n Ti
me 22
24
26
Prop
ag 28
30
32
Backscattered signal modulated by rhythmic variations of the breast due to breathingPr
opag 28
30
32
Prop
ag 28
30
32
Backscattered signal modulated by rhythmic variations of the breast due to breathing
Breathing personBreathing personBreathing personBreathing person
Observation Time, s110 120 130 140
32
Observation Time, s110 120 130 140
32
Observation Time, s110 120 130 140
32
on T
ime
[ns] 10
20
on T
ime
[ns] 10
20
Prop
agat
io 30
40Prop
agat
io 30
40Radar data after enhancement of breathing activity
Slide 35Technische Universität Ilmenau FG Elektronische Meßtechnik
2008 35Breathing rate [Hz]
0.2 0.4 0.6 0.8 1 1.2
50
Breathing rate [Hz]0.2 0.4 0.6 0.8 1 1.2
50 of breathing activity
Through-Wall MeasurementsThrough-Wall Measurements
Light concrete ll
Wooden wall
wall
Bricks TimberBricks Timber
Hand held
TilTile
Hand held device
Tile
FloorSlide 36
Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
Floor
Courtesy RADIOTECT project
Larvae detectionLarvae detection
Hylotrupes bajulusMeasurement set-up
Bi-static radar
Wood with larvaWood with larva
Slide 37Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
Larvae detectionLarvae detection
Radargram after Background removal
ns] 16
Radargram after Background removal
ROI (region of interest)
rip ti
me
[n 182022
Movement of the larva( g )
OI
roun
d tr
2426
Movement of the operator (far away from the test object)
0 6
0.8
1
rgy
of R
O
observation time [s]0 20 40 60 80 100 120 140 160 180
0.2
0.4
0.6
lised
ene
r
0 20 40 60 80 100 120 140 160 1800
observation time [s]norm
al
Slide 38Technische Universität Ilmenau FG Elektronische Meßtechnik
2008 38
ConclusionsConclusions
• UWB sensor application offers clear advantage over other radar, optical and ultrasound sensors.
• Frequency regulation not optimal for sensor li tiapplication.
• Low power, high clock rate integrated circuit technolog req ired (SiGe)technology required (SiGe).
• Huge absolute and relative bandwidth requires paradigm shifts from narrowband to widebandparadigm shifts from narrowband to wideband principles.
• Sensor cooperation and spatial distributedSensor cooperation and spatial distributed processing (sensor networks).
Slide 39Technische Universität Ilmenau FG Elektronische Meßtechnik
2008
AcknowledgementAcknowledgement
Contributions by Dr. Sachs, Dr. Zetik, Dr. Hirsch, Dr. Helbig
Ultra-Wideband Radio Technologies for gCommunications, Localization and Sensor Applications
Slide 40Technische Universität Ilmenau FG Elektronische Meßtechnik
2008