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Remote sensing and SAR radar images processing
Physics of radar
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TABLE OF CONTENTS
Potentialities of radar Radar transmission features Propagation of radio waves Radar equation Surface scattering mechanisms Volumetric scattering mechanisms Penetration depth of waves in observed media
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Potentialities of radar
‘All-weather’ observationsystem (active system).
Sensitivity to dielectric properties of medium (water content, humidity), and to its roughnessthe radar response when the moisture and/or when roughness
Sensitivity to geometrical structures with scales of the same order as the wavelength
Penetration capabilities estimation of plant biomass,
observation of buried structures, cartography of subsoils, etc.penetration when the frequency
Sensititivity to topography (related to the acquisition geometry)
not sensitive to sun lightening, not sensitive to cloud coverOther advantages with respect to optics: ranging (simple and accurate geometric modeling),
detection capacity (even at medium resolution)
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Drawbacks: speckle (difficult visual interpretation)
Sensitive to: roughness relief (slope) humidity metallic and artificial objects
Introduction Imaging radar features
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With respect to optics:
day/night imaging capacity (x 2) insensitive to cloud cover ( x 5)
10 times more images available Faster information access
Multi-Incidence - Multi-Resolution
With a constellation of 4 SAR Satellites : information access delay shorter than 24h (from decision to interpretation)
Introduction (2/2)Accessibility
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Radar transmission features
The frequency (carrier frequency + bandwidth)
The propagation direction (Ex: ERS: 23°)
The transmitted power (Ex: ERS: ~ 5 kW pic) impact on image quality
The polarization
)(cm1.0 1 10 100
)(GHzf300 30 3 3.0
Ku Ka X L PSC
h
v
k
h
n
v
hk n
hHorizontal polarizationRADARSAT type
Vertical polarizationERS type
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))..ˆ(.(exp.),( trkjEtrE O
Spatial-temporal variations of the electric field during propagation:
ktrHtrE ˆ),(),(
Configuration of electromagnetic fields in free space:
ktrHtrE ˆ),,(),,( form a direct trihedral
Radar transmission featureselectric field
magnetic field
E
H
x
y
z energy propagation
k
Propagation of radio waves Maxwell’s equations
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i: incident flux
Portion of backscatteredpower
pointtarget
i = incident flux = incident power per area unit normal to incident beam:
Ge: Transmitting antenna gain; R: Radar-target distance
Portion of backscattered power:
Power received on the receiving antenna:
Effective area of receiving antenna
²4 Ri
4
² GrAeff
Radar equation (1/4) Case of point targets (1/2)
Portion of energy sent backby the point target =
Radar reflective area (SER )
²4.
RPemittedGei
AeffR
P i ²4
.received
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The radar equation is derived from the transmission-backscattering-reception process:
transmission receptionbackscattering
Radar equation Case of point targets
system propagation
Target (radar equivalent cross-
section)Unit: m²
Set of terms determinedby calibration procedures
4²
²4.
²4.received
Gr
RRGePemittedP
43
²4
.receivedR
GrGePemittedP
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The radar backscattering coefficient (marked σo) represents the average value of the Radar reflective area per area unit (case of an extended target, for example on the scale of a pixel):
dSdo If area is homogeneous: S
o
PemittedPko received
σ is expressed in m², σo is expressed in m²/m²
)(log.10)dB( o10
o
Representation of 0 on a logarithmic scale:
Value dynamics ~ -40 dBm²/m² +10 dBm²/m²
Coefficient k is determined by calibration
Radar equation Case of extended targets
‘ 0 ’ means normalizationin relation to an area
Unit: dBm²/m²
Unit: m²/m²
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²/²00 mdBm²/²0 mdBm
²/²00 mdBm²/²00 mdBm
Radar equation (4/4) Case of extended targets (2/2)
Behavior and typical values of 0
0 dBm²/m²
-7 dBm²/m²
-10 dBm²/m²
-15 dBm²/m²
-22 dBm²/m²
20 dBm²/m²
50 dBm²/m²
Forest
Vegetation
Short grass
Concrete, bitumen, etc.
Urban areas, etc.
Point targets: vehicles, ships, etc.
0
Noise image limit
Depends on incidence Depends on frequency
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The radar backscattering coefficient o (quantity of energy returning to the radar) depends on:• The surface roughness• The dielectric permittivity of medium (related to the water content)
o when roughness o when moisture
Rough dry soil Wet smooth soil=
Indetermination between the moisture and roughness level based on knowledge of 0 alone
Surface scattering mechanisms (3/4) Case of a rough dielectric surface (1/2)
Medium 2 homogeneous: no volume scattering
roughness generates backscattering (part of energy returning to the radar). The dielectric nature produces penetration.
medium 2
medium 1
hence indetermination:
o ~ f (roughness) . g (r )
moisture
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Rayleigh’s criterion:
• When the phase difference between the 2 reflected waves (at A and B) due to propagation is < /2, the surface is considered as smooth.
Now: = 2/ = 2/hcos smooth surface if: h < λ/8/cosθ
•Δ > π/2 rough surface
Surface scattering mechanisms (4/4) Case of a rough dielectric surface (2/2)
Quantification of roughness, Rayleigh’s criterion: A surface is not intrinsically smooth orrough from the radar point of view. This concept is meaningful only if referred to wavelength.
zinck
h
A
B
Remark: in C-band (l=5.6 cm), condition (1) gives h < 0.8 cm at 23° (ERS-1): all natural surfaces are rough under these observation conditions.
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7
2
43
16 5
1) Crown scattering
3) Trunk-soil interaction
5) Direct soil scattering
2) Trunk scattering
4) Attenuated soil scattering
6) Trunk-branch interaction
7) Soil-branch interaction
Examples of main backscatteringmechanisms on the forest
Volumetric scattering mechanisms Case of the forest
Volume backscattering mechanisms generally rely on interaction mechanisms which are highly complex and still not well-known. Main trends:
Backscattering coefficient when vegetation volume (biomass)
Wavelength penetration when frequency , i.e. when wavelenght
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SIR-C image Landes Forest, FranceL-Band, 26° (0
HV)
High penetration capabilitiesin canopy. Application:Biomass cartography(CESBIO origin )
L-Band = 23 cm
20 m
C-Band = 6 cm
6 m
X-Band = 3 cm 1 m
Penetration depth of waves in observed media Penetration capabilities of radar waves versus wavelength
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0 33 65 95 130 150
Biomass (tons/ha)L-band, HV-polarisation, 26°
-24
-22
-20
-18
-16
-14
0 33 65 95 130 150Biomass (tons/ha)L-band, VV-polarisation, 26°
-12
-11
-10
-9
-8
-7
-6
vv (d
Bm
2 /m2 )
o
0 33 65 95 130 150Biomass (tons/ha)C-band, VV-polarisation, 26°
-10
-8
-6
-4
-2
vv (d
Bm
2 /m2 )
o
hv (d
Bm
2 /m2 )
o
Experimental results show that radar sensitivity to biomass is a complex mechanism depending jointly on frequency and polarisation
SIRC data, Landes forest, France (origin : CESBIO)
RADAR SENSITIVITY TO BIO-MASS
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• The visibility of a grass runway in the right image demonstrates the volumetric scattering characteristics (thus the penetration characteristics) in L-Band. For the same reason, forest plots are brighter in L-Band. Surface roughness is better reflected in X-band. Also apparent is the rather low image constrast in X-Band as compared to L-Band..
From: http://atlas.op.dlr.de/ne-hf/projects/ESAR/igars96_scheiber.html
X-Band ESAR L-Band ESAR
Penetration depth of waves in observed media Radar signature differences between X-band (10 GHz) and L-band (1.25 GHz)
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Centimetric wavelength (2 cm) S-Band Metric wavelength (290 cm) P-Band
The right image is an example of low-frequency radar imagery acquired in the P-Band (100 MHz).Although of lower image quality compared to the left image, it makes it possible to see underground structures, in this case pipeline segments (VNIIKAN Siberian campaign -1994)
Penetration depth of waves in observed media Capabilities of low-frequency imaging radars (P-Band)
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Soil humidity ( gr/cm3 )
pene
trat
ion
( cm
)
0
2
4
6
8
10
12
14
16
18
0 10 20 30 40 50 60
Left: IR optical image over the same region
Left: SIR-C multi-frequency radar image (Nile)(R : CHH, G : LHV, B: LHH). Inverse LUT
Below: Wave penetration in bare soil for different SAR bands as a function of humidity bande L ×bande C bande X
From : www.jpl.nasa.gov/radar/sircxasr
RADAR SOIL PENETRATION
scattereroneofoncontributiresponsepixel
The speckle noise, consequenceof a coherent illumination (1/2)
e
m1npixel
e
2npixel m
Image SETHI, bande C, 3 m
The speckle noise, consequence of a coherent illumination (2/2)
The speckle noise is a multiplicativenoise
Low radiometry : low noise
Large radiometry : large noise
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SAR principle / Image Quality / Processing
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CONTENT
Introduction
Reminders: detection radar / antenna scattering Side-Looking Airborne Radar (SLAR) Range processing Synthetic Aperture Radar (SAR) Azimuth processing SAR ambiguities Moving targets Special modes (SAR) Image Quality: Radiometry Image Quality: Geometry Image Quality: localization Processing at CNES: PRISME
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Pulses
Range
azimuth
range
azimuthrange
Radar screen
target
t0
Pulse transmission chronogram
• The range information comes from the time needed by the pulse to travel way and back
Reminder: Detection radars
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L
Angular aperture(horizontal plane)
L
Antenna length (horizontal direction)
Wavelength
The larger the antenna, the narrower the aperture (resolution )
'L
Reminder: Antenna scattering
Numerical example:L 4m, R 4 km (airborne radar), 3 cm (X band) resolution 30 m
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SLAR: Side-Looking Airborne Radar (1/9)
Linear displacement of the antenna along the track (aircraft)
Azimuth direction
Range direction
Pulses
s
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rrange
razimuth
SLAR: Why « Side-Looking » ? (2/9)
Left/Right Range ambiguity
Removal ofLeft/Right Range ambiguity
3D representation
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Numerical example:(airborne example)
L = 4 mW = 5 cm= 20-60°H = 3000 mSwath = 4 kmRazi = 25 - 45 m
SLAR azimuthresolution 35m
H
L
W
Azimuthdirection
Rangedirection
Transmittedpulse
s
Echoes
Swath Razi
Chronogram: pulses versus time
Prf: Pulse Repetition Frequency
Remark: Azimuth pixel size = S / Prf
SLAR (3/9)Azimuth resolution
L Azimuth resolution: Rθ, with
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In the case of a Dirac transmission, range resolution = pixel size in range: it depends only on the sampling frequency Fs. This is always true for the range pixel size (by construction), but not for the resolution if the pulse is not a Dirac
Transmitted pulse (Dirac)ideal time resolution
Sampling of the received echo (with Fs frequency) = sampling in the spatial domain(generation of an image line)
Fsc2
: range (distance) pixel size inthe radar geometry, by constructionof an image line
sin2 Fsc : ground range pixel size
SLAR (4/9) ‘ Ideal ’ range resolution: Case of a Dirac pulse transmission
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Pulse duration distance (or range) resolution: and ground range resolution: 2/c
PRF/1
SLAR (5/9) ‘ Real ’ range resolution: case of a pulse transmission of duration (1/2)
Practically, for power budget reason, the pulse duration is . The resulting resolution is dominated by the Factor as shown in next slide
2c
(Numerical example ERS, 37 s, range resolution 5 km)
sin2c
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PRF/1
t0
Modulation bandwidth: chirpB
equivalence
PRF/1
compchirpcomp B/1
Numerical example ERS, 37 s, Bchirp=15.5 MHz comp=64 ns
Achieved range resolution (slant range):
Achieved range resolution (ground range):
SLAR (7/9) Improvement of range resolution: pulse compression
chirpdist Bcs
.2Re
In order to improve distance resolution, the transmitted pulse is frequency modulated (over a bandwidth Bchirp): this can be shown to be equivalent to the transmission of a shorter pulse:
)sin(..2_ iBcRes chirpsoldist
)sin(/ i
i
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time
Compressed Pulse
duration
t1 t2t0
swath
Numerical example: ERS
SLAR (8/9) Pixel size vs. Resolution in range
The pixel size is defined by the sampling frequency Fs
The range resolution is defined by the modulation Bandwidth Bchirp
comp
sin2 Fsc
Fsc2
MHzB comp 5.151 mRes rangeslant 7.9_
mtoRes rangeground 3222_
MHzFs 96.18
mPixel rangeslant 9,7_
mtoPixel rangeground 1826_
Pixel size
resolution
The pixel size is generally “built”slightly smaller than
the resolution: FsBchirp
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The antenna progression alongthe orbit allows to observe each given point at different times
v Azimuthdirection
Range direction Resolution improvement
in the azimuth direction
Pulse transmission
Synthetic Aperture Radar (SAR) Principle (1/12)
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Coherent adding of successively received echoes Resolution gain in the azimuth direction (Ex: ERS: 5 km 5 m)
aziS
T
azi
'T
durationonilluminati v
T 'T
v
Equivalence
vdurationonilluminatiL
The moving small antennais equivalent to a long fixed antenna(size , directivity , resolution )
The compression rate Na equals the number of coherently added echoes (complex addition). It is the resolution gain in the azimuth direction
SAR
SyntheticAperture
SAR Principle (2/12) Signal processing in azimuth: principle (1/2)
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Fd > 0
Fd = 0
Fd < 0
SAR Principle (4/12) Signal processing in azimuth: Doppler analysis (1/5)
The range variations between a target and the sensor produce a linear Doppler effect of the transmitted pulse(quadratic distance&phase variations with time linear frequency variations with time in a frequency band: Doppler Bandwidth)
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Target-antenna range variations during the illumination time produce a Doppler effect, resulting in spreading the backscattered energy over a bandwidth
dtdf dop
21
where:
2/10 ²²²22 tvR
Rtvf dop
²2
RTvB dop
int²2
vLRT 1int
LvB dop 2
Doppler frequency
Instantaneous phase
Total Dopplerbandwidth
2L
Bdopvresolutionspatial
LRRS azi
T
R
azi
'T
L
intT :duration onilluminati
v
LvB dop 2
Position origine des temps
SAR Principle (5/12) Signal processing in azimuth: Doppler analysis (2/5)
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Doppler excursion versus time(case of a zero Doppler centroïd)
Frequency spectrum in azimuth(antenna pattern modulation)
f
azifS )(
dopB
lookcentral
lookbackward
v
2/intT
dopBt
dopf
2/intT
lookforward
intT
SAR Principle (6/12) Signal processing in azimuth: Doppler analysis (3/5)
Rtvf dop
²2
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radar acquisition:range discriminationof the space: A’,B’,C’
optical acquisition:angular discriminationof the space: A”,B”,C”
Image quality: geometry (1/4) radar versus optics
(From Elachi, 1989)
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• ‘shortening’ of slopes facing the radar• ‘stretching’ of slopes oppositely oriented to the radar
Image quality: geometry (2/4) geometrical artifacts related to the vision in range
The foreshortening effect
radar
Radar discrimination
capacity
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shadow
Layover effect on airborne image “Sethi” Tour Eiffel, Paris, C band (resolution: 3m)
Radar trajectory
Loo
k di
rect
ion
Image quality: geometry (3/4) geometrical artifacts related to the vision in range
The layover effect
A
BA’
B’
The point A (top) is projected before B (base) in the
direction of the radar pass
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Standard beam position 1: acquired Feb.12, 1996
From: RADARSAT Geology Handbook(RADARSAT International), 1997
Image quality: geometry (4/4) geometrical artifacts related to the vision in range
example of foreshortening, layover and shadows
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ENVISAT MERIS Not quite the same geometry…!!
Where is Spain?Where is the North? Where did the
satellite pass????
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