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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????