Remote sensing and SAR radar images processing Physics of radar

(1)

Remote sensing and SAR radar

images processing

(2)

TABLE OF CONTENTS



Potentialities of radar



Radar transmission features



Propagation of radio waves



Radar equation



Surface scattering mechanisms



Volumetric scattering mechanisms

(3)

Potentialities of radar

‘All-weather’ observation system (active system).

Sensitivity to dielectric properties of medium (water content, humidity), and to its roughness

the 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 cover

Other advantages with respect to optics: ranging (simple and accurate geometric modeling),

(4)



Drawbacks:



speckle

(difficult visual interpretation)



Sensitive to:



roughness



relief (

slope

)



humidity



metallic and

artificial objects

Introduction

(5)

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

(6)

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

)

(

cm



1

.

0

1

10

100

)

(

GHz

f

300

30

3

0

.

3

Ku

Ka X

C

S

L

P

hˆ vˆ kˆ hˆ

n

ˆ

vˆ hˆ kˆ

n

ˆ

hˆ Horizontal polarization RADARSAT type Vertical polarization ERS type

(7)

))

.

ˆ

(

.

(

exp

.

)

,

(

r

t

E

j

k

r

t

E



O





 Spatial-temporal variations of the electric field during propagation:

k

t

r

H

t

r

E

(

,

)







(

,

)



ˆ

 Configuration of electromagnetic fields in free space:

k

t

r

H

t

r

E

(

,

),

(

,

),

ˆ

_{form a direct trihedral}

Radar transmission features

electric field magnetic field

E



H



x

ˆ

y

ˆ

z

ˆ

energy propagation

k

ˆ

Propagation of radio waves



Maxwell’s equations

(8)

 _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 ² 4 R i    





4

²





Gr

Aeff

Radar equation (1/4)

 Case of point targets (1/2)

Portion of energy sent back by the point target = Radar reflective area (SER )

²

4

.

R

Pemitted

Ge

i







Aeff

R

P



_i



²

4

.

received







(9)

The radar equation is derived from the transmission-backscattering-reception process:

transmission

backscattering

reception

Radar equation

 Case of point targets

system propagation

Target (radar equivalent

cross-section) Unit: m²

Set of terms determined by calibration procedures











4

²

4

.

²

4

.

received





Gr



R

Ge

Pemitted

P





















₃ ₄

²

4

.

received

R

Gr

Ge

Pemitted

P

(10)

reflective area per area unit (case of an extended target, for example on the scale of a pixel):

dS d o



 If area is homogeneous: S o





Pemitted

P

k

o





received



 σis expressed in m², σo is expressed in m²/m² ) ( log . 10 ) dB ( o 10 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 normalization in relation to an area

Unit: dBm²/m²

(11)

²

/

²

0



dBm

m



²

/

²

0





dBm

m



² / ² 0 0  dBm m 

²

/

²

0



dBm

m



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

(12)

• 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

(13)

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 or rough from the radar point of view. This concept is meaningful only if referred to wavelength.

z

ˆ

 inc

k

ˆ

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.

(14)

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 backscattering

mechanisms 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) 

(15)

Landes Forest, France

L-Band

, 26° (0

HV)

High penetration capabilities in 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

(16)

© copyright CNE 0 33 65 95 130 150 Biomass (tons/ha) L-band, HV-polarisation, 26° -24 -22 -20 -18 -16 -14 0 33 65 95 130 150 Biomass (tons/ha) L-band, VV-polarisation, 26° -12 -11 -10 -9 -8 -7 -6 vv (dBm 2 /m 2 )  o 0 33 65 95 130 150 Biomass (tons/ha) C-band, VV-polarisation, 26° -10 -8 -6 -4 -2 vv (dBm 2 /m 2 )  o hv (dBm 2 /m 2 )  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)

(17)

• 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

(18)

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

(19)

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

(20)

scatterer one of on contributi response pixel

The speckle noise, consequence

of a coherent illumination (1/2)

 

e



m



1  n pixel

e



2  n pixel



m

(21)

Image SETHI, bande C, 3 m

The speckle noise, consequence of a coherent illumination (2/2)

The speckle noise

is a multiplicative

noise

Low radiometry :

low noise

Large radiometry :

large noise

(22)

(23)

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

(24)

azimuth

range

Radar

screen

target

t 0

Pulse transmission chronogram

• The range information comes from the time needed by the pulse to travel way and back

(25)

L







Antenna length (horizontal direction) Wavelength

The larger the antenna, the narrower the

aperture (resolution )

' L



Reminder: Antenna scattering

Numerical example:

(26)

SLAR: Side-Looking Airborne Radar (1/9)

Linear displacement of

the antenna

along the track (aircraft)

Azimuth direction

Range direction

Pulses

(27)

r_azimuth

SLAR: Why « Side-Looking » ? (2/9)

Left/Right Range ambiguity

Removal of

Left/Right Range ambiguity

(28)

SLAR azimuth

resolution



35m

 H L W Azimuth direction Range direction Transmitted pulse

s



Echoes

Swath

R

_azi Chronogram:

pulses versus time

Prf: Pulse Repetition Frequency

Remark: Azimuth pixel size = S

/

Prf

SLAR (3/9)



Azimuth resolution

L







Azimuth resolution: R

θ

, with

(29)

© copyright CNE 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)



Fs c



2

:

the radar geometry, by construction

range (distance) pixel size

in

of an image line



sin 2Fs

c

:

ground range pixel size

SLAR (4/9)

(30)

Pulse duration   distance (or range) resolution: and ground range resolution:

c





/

2



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

2





c

(Numerical example ERS,   37 s, range resolution  5 km)





sin

2



c

(31)



PRF / 1 t 0

Modulation bandwidth:

B

chirp

equivalence PRF / 1 comp



comp chirp

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

chirp dist

B

c

s

.

2

Re



 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 _ i B c Res_dist _sol  _chirp

 ) sin( / i  i

(32)

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



 sin 2Fs c Fs c  2

MHz

B



1



_comp



15

.

5

m

Res

_slant_{_}_range



9

.

7

m

to

Res

_ground_{_}_range



22

32

MHz

Fs



18

.

96

m Pixel _slant _{_}_range  7,9

m

to

Pixel

_ground _{_}_range



26

18

Pixel size

resolution

The pixel size is generally

“built”slightly smaller than

(33)

The antenna progression along the orbit allows to observe

each given point at different times

v



_Azimuth

direction

Range

direction _{Resolution improvement}

in the azimuth direction

Pulse transmission

(34)

Coherent adding of successively received echoes _{Resolution gain in the azimuth direction}

(Ex: ERS: 5 km  5 m) azi S

T

azi



'

T

duration on illuminati v

T

T '

v



Equivalence

v duration on illuminati L 

The moving small antenna is 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

Synthetic Aperture

SAR Principle (2/12)

(35)

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)

(36)

backscattered energy over a bandwidth

dt d f dop       2 1 where:





1/2 0 ² ² ² 2 2   R  v t        R t v f dop       ² 2 _ R T v B dop      int ² 2 v L R T int     1  L v B dop  2  Doppler frequency Instantaneous phase Total Doppler bandwidth  2 L Bdop v resolution spatial    L R R S azi  



 



T

R

azi



'

T

L int T : duration on illuminati v L v B dop  2  Position origine des temps

SAR Principle (5/12)

(37)

Doppler excursion versus time (case of a zero Doppler centroïd)

Frequency spectrum in azimuth (antenna pattern modulation)

f azi f S ( ) dop

B

look central look backward

v



2 / int T dop B t dop f 2 / int T  look forward int T

SAR Principle (6/12)



Signal processing in azimuth: Doppler analysis (3/5)

R t v f dop       ² 2

(38)

radar acquisition:

range discrimination

of the space: A’,B’,C’

optical acquisition:

angular discrimination

of the space: A”,B”,C”

Image quality:

geometry

(1/4)



radar versus optics

(39)

(

From Elachi, 1989

)

•

‘

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

(40)

shadow

Layover effect on airborne image “Sethi” Tour Eiffel, Paris, C band (resolution: 3m)

Radar trajectory

Look dir

ection

Image quality: geometry (3/4)



The

layover

effect

A

B

A’

B’

The point A (top) is projected

before B (base) in the

(41)

position 1:

acquired Feb.12, 1996

From: RADARSAT Geology Handbook

(RADARSAT International), 1997

Image quality: geometry (4/4)



(42)

ENVISAT MERIS

Not quite the same

geometry…!!

Where is

Spain?Where

is the North?

Where did the

satellite

pass????