Microwave Remote Sensing: Principles and
Applications
•
Outline
– Introduction to RSL at the University of Kansas
– Introduction and History of Microwave Remote Sensing
– Active Microwave Sensors
• Radar Altimeter.
• Scatterometer.
• Imaging Radar.
– Applications of Active Sensors
•
•
•
•
•
•
•
•
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Sea ice.
Glacial ice
Ocean winds.
Soil Moisture.
Snow.
Vegetation.
Precipitation.
Solid Earth.
University of Kansas
Microwave Remote Sensing: Principles and
Applications
• Passive Microwave Sensors
– Radiometers
• Traditional
• Interferometer
• Polarimetric Radiometer
• Application of Passive Microwave Sensors
•
•
•
•
•
•
•
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Sea ice.
Glacial ice
Soil Moisture.
Atmospheric sounding
Snow.
Vegetation.
Precipitation
University of Kansas
Radar Systems and Remote Sensing
Laboratory
Windvector
Measurements over
the Ocean
Radar at 14 GHz.
Concept developed at
KU.
USA, Europe and
Japan are planning
to launch satellites
to obtain data
continuously.
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University of Kansas
Radar Systems and Remote Sensing
Laboratory
Founded in 1964.
4 Faculty members, 20 Graduate students - Ph. D & M.S.
4-6 Undergraduate students, 2 Staff
Now satellites based on concepts developed at RSL are in
operation.
NSCAT, QUICKSCAT- Radars to measure ocean surface winds.
ADEOS-2 (JAPAN), Europeans Met Office is planning to launch
satellite to support operational applications.
ScanSARRadarsat- Canadian satellite
Envisat - European
SRTM -Shuttle Radar Topography Mission.Radar Systems
and Remote Sensing Laboratory
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University of Kansas
Radar Systems and Remote Sensing
Laboratory
• Shuttle Radar Topography
Mission (SRTM)
– to collect threedimensional
measurements of the
Earth's surface.
– Acquired data to obtain
the most complete
near-global mapping of
our planet's topography
to date.
– This would not have
been possible without
ScanSAR operation--concept developed at
KU.
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University of Kansas
ITTC– Information Technology &
Telecommunication Center
• Communications academic emphasis and
research programs established in 1983.
• Now RSL is a part of the Center
• Graduated students
– degrees in EE, CS, CoE, Math
• 29 faculty, 15 staff researchers, 6 Center
staff
• Current student population ~ 130
– ~ 13 Ph.D., ~81 M.S., ~37 B.S.
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University of Kansas
EM Spectrum
• Microwave region
• 300 MHz – 30 GHz.
Millimeter wave
• 30 GHz – 300 GHz.
IEEE uses a different
definition
• 300 MHz – 100 GHz
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University of Kansas
Microwave Remote Sensing: Principles and
Applications.
• Advantages
– Day/night coverage.
– All weather except during
periods of heavy rain.
– Complementary
information to that in
optical and IR regions.
• Disadvantages
– Data are difficult to
interpret.
– Coarse resolution except
for SAR.
11/18/02
University of Kansas
Microwave Remote Sensing— history
• US has a long history in Microwave Remote Sensing.
– Clutter Measurement program after the WW-II.
• Ohio State University collected a large data
base of clutter on variety of targets.
– Earnest studies for the remote sensing of the
earth can be considered to have began 1960s.
• In 1960s NASA initiated studies to investigate
the use of microwave technology to earth
observation.
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University of Kansas
Microwave Remote Sensing— history
• The research NASA and other agencies initiated resulted in:
– Development of ground-based and airborne sensors.
– Measurement of emission and scattering characteristics of
many natural targets.
– Development of models to explain and understand measured
data.
– Space missions with microwave sensors.
• NIMBUS
– Radiometers.
• SKYLAB
– Radar and Radiometers
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University of Kansas
Microwave Remote Sensing
• Radar
Applications
– Radio Detection and
Ranging.
– Texts:
Civilian
Navigation and
tracking
• Skolnik, M. I.,
Introduction to Radar
Systems, McGraw Hill,
1981.
• Stimson, G. W.,
Introduction to Airborne
Radar, SciTech
Publishing, 1998.
Search and
surveillance
Imaging &
Mapping
Military
Navigation and
tracking
Search and
surveillance
Weather
Imaging &
Mapping
Sounding
Weather
Probing
Proximity fuses
Remote sensing
Counter measures
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University of Kansas
Review – EM theory and Antennas
• Propagation of EM
waves is governed by
Maxwell equations.
• For time-harmonic
variation we can
write the above
equations as
D
 H  J 
t
B
 E  
t
.B  0
.D  
  H  J  j E
  E   j H
.B  0
.D  
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University of Kansas
EM Theory
• Helmholtz Equation
– From the four
Maxwell equations,
we can derive vector
Helmholtz equations
– For each component
of E and H field we
can write a scalar
equation
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 E  2E  0
2
 H  2 H  0
2
where   
 2 Ex  2 Ex  2 Ex


  2 Ex  0
2
2
2
x
y
z
2Ey
x
2

2Ey
y
2

2Ey
z
2
  2Ey  0
 2 Ez  2 Ez  2 Ez
2




Ez  0
2
2
2
x
y
z
University of Kansas
Uniform plane wave
Amplitude and phase are constant on
planes perpendicular to the direction of
propagation.
TEM case– no component in the direction
of propagation.
For a TEM wave propagating in z direction
Ez = 0 and Hz =0
Ex(z,t) = Eo e-αz Cos(ωt-jβz)
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University of Kansas
EM theory
• α and β are
determined by
material properties.
• Materials are
classified as
insulators and
conductors
    j 
For a loss - loss medium   


2 
   

Fresh wate r ice, dry snow and
dry soil are examples of low - loss media.
For a conductor   
  
–
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j   j
University of Kansas

2
EM Theory
• Reflection and
refraction
θi
– Whenever a wave
impinges on a
dielectric interface,
part of the wave will
be reflected and
remaining will be
transmitted into the
lower medium.
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University of Kansas
θr
θt
EM Theory--Scattering
• Microwave Scattering from a
distributed target depends on
– Dielectric constant.
– Surface roughness.
– Internal structure.
• Homogeneous
• Inhomogeneous
– Wavelength or Frequency.
– Polarization.
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University of Kansas
Microwave Scattering
• Surface scattering
– A surface is classified as
smooth or rough by
comparing its surface
height deviation with
wavelength.
• Smooth h < λ/32
cos(θ)
• For example at 1.5
GHz and = 60 deg.,
• h < 1.25 cm
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University of Kansas
θi
θr
Smooth surface
Moderately rough
surface
Very rough surface
Microwave Scattering
• Rough surface scattering
10
0
Scattering
coefficient, dB
-10
Rough surface
-20
Slightly rough surface
-30
Relatively smooth surface
0
10
20
30
40
50
Incidence angle,
deg
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University of Kansas
Microwave Scattering
• Volume scattering
– Material is
inhomogeneous such
as
•
•
•
•
Snow
Firn
Vegetation
Multiyear ice
i
r
t
i
r
 To   s0  T 2 ( ) vo ( t )
t
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University of Kansas
Microwave Scattering
• Surface scattering models
– Geometric optics model
• Surface height standard deviation is large compared to the
wavelength.
– Small perturbation model
• Surface height standard deviation is small compared to the
wavelength.
– Two-scale model
• Developed to compute scattering from the ocean
– Small ripples riding on large waves.
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University of Kansas
Antennas
• Antennas are used to couple electromagnetic
waves into free space or capture
electromagnetic waves from free space.
• Type of antennas
– Wire
• Dipole
• Loop antenna
– Aperture
• Parabolic dish
• Horn
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University of Kansas
Antennas
• Antennas are characterized
by their:
– Directivity
• It is the ratio of maximum
radiated power to that
radiated by an isotropic
antenna.
– Efficiency
• Efficiency defines how
much of the power is the
total power radiated by the
antenna to that delivered to
the antenna.
– Gain
• It is the product of
efficiency and directivity
– Beamwidth
• Width of the main lobe at
3-dB points.
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dipole
Antenna gain
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University of Kansas
Antennas
• An array of antennas
is used whenever
higher than
directivity is
needed.
– Can be used to
electronic scanning.
– Most of the SAR
antennas are arrays.
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University of Kansas
Antenna Array
R1  Ro  d sin  
• Let us consider
simple array
consisting of
isotropic radiators.
R1
Ro
d

P
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University of Kansas
R  d sin  
2
 
d sin  

2 ( Ro  d sin 
j
  j 2R0



Et  Eo  e   e



2R0
d sin 
d sin 
d sin 
j
j
j
j




e   e

Et  Eo e  e




Et  2 Eo e
j
2R0

e
j
d sin )

cos
d sin  
)

 2d sin   
Et   Eoi cos




i
If we increase from 0 to 90 degrees
and reduce the resulting expression .
sinx
Et 
x
Radar Principles
• Radar classified
according to the
trasmit waveform.
Radar
– Continuous
• Doppler
• Altimeter
• Scatterometer
Non-pulsed
CW
FM-CW
Non-Coherent
Coherent
MTI
SAR
Pulse Doppler
– Pulse
• Wide range of
applications
11/18/02
Pulsed
University of Kansas
Radar Principles
• Radar measures
distance by
measuring time delay
between the
transmit and
received pulse.
– 1 us = 150 m
– 1 ns = 15 cm
Pulse
Radar
Radar
c
2
  time delay between tr ansmission
R
and reception
c  velocity of propagatio n
R  Range to the jet.
11/18/02
University of Kansas
Radar— principle
• Unambiguous range
and Pulse Repetition
Frequency (PRF)
– PRF also determines
the maximum doppler
we can measure with
a radar— SAR.
– PRF > 2 fdmax
PRI
2.12
4.16
PRI  T
PRF , f p 
Run 
University of Kansas
1
T
C
2 fp
For a radar with f p  1500 Hz
R un 
r 
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0.47
3x108
 100 km
2 x1500
c p
2
, r  150m for  p  1 s
Radar—Principle
• Radar equation
•
•
•
PT
GT
R
Power density at the target is given byP
PG
Pd  T T2
4R
Target wit h radar cross section,  , intercepts
a part of this signal and reradiates
in the direction of the radar.
PG
Pdr  T T2 
4R
Reradiated power incident on the antenna is given by
PG
1
Pri  T T2 
4R
4R 2
The receive antenna with an effective aperture, Ae, incident signal and it is given by
Ae
PG
P r  T T2 
4R
4R 2
P G G 2
Pr  T T 3R 4
(4 ) R
4A
where GR  2 e
•
•
•
For a monostatic radar
GT = GR
Radar sensitivity is determined
by the minimum detectable
signal set by the receiver noise.
No = kTBF
F= noise figure
Signal-to-noise ratio

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University of Kansas
S
P
P T GT2 2
 r 
N N o (4 ) 3 R 4 KTBF
Rmax  1
4
P T GT2 2
S
(4 ) 3 KTBF
N
Microwave Remote Sensing
• Radar cross section
characterizes the
size of the object as
seen by the radar.
  Lim R 4R
Where
Es = scattering field
Ei = incident field
r
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University of Kansas
2
2
Es
Ei
2
  r
2
Radar Equation
• A distributed target
contains many
scattering centers
within the
illuminated area. It
is characterized by
radar cross section
per unit area, which
is refereed to as
scattering
coefficient
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  oA
 o  scattering coefficient
A  Illu min ated area
e
o
PT GT22 0 A
Pr 
(4 )3 R 4
a
R

 


R cos( 0 ) tan( o  e )  tan( o  e )  R tan( a )
2
2
2 
2

If  0  1 &   1
A
A


4
University of Kansas
R2ea
Radar Equation
PT GT2 2 0 R e R a
Pr 
(4 ) 3 R 4
4
PT GT2 2 0  e  a
Pr 
(4 ) 2 R 2 16
For a distributed power received falls off as 1/R2
For a point target power received falls off as 1/R4
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University of Kansas
Antenna Array
R1  Ro  d sin  
• Let us consider
simple array
consisting of
isotropic radiators.
R1
Ro
d

P
11/18/02
University of Kansas
R  d sin  
2
 
d sin  

2 ( Ro  d sin 
j
  j 2R0



Et  Eo  e   e



2R0
d sin 
d sin 
d sin 
j
j
j
j




e   e

Et  Eo e  e




Et  2 Eo e
j
2R0

e
j
d sin )

cos
d sin  
)

 2d sin   
Et   Eoi cos




i
If we increase from 0 to 90 degrees
and reduce the resulting expression .
sinx
Et 
x
Antenna Array
R1  Ro  d sin  
• Let us consider
simple array
consisting of
isotropic radiators.
R1
Ro
d

P
11/18/02
University of Kansas
R  d sin  
2
 
d sin  

2 ( Ro  d sin 
j
  j 2R0



Et  Eo  e   e



2R0
d sin 
d sin 
d sin 
j
j
j
j




e   e

Et  Eo e  e




Et  2 Eo e
j
2R0

e
j
d sin )

cos
d sin  
)

 2d sin   
Et   Eoi cos




i
If we increase from 0 to 90 degrees
and reduce the resulting expression .
sinx
Et 
x
Microwave Remote Sensing: Principles and
Applications— History
• Active Microwave sensing
– Studies related to active sensing of the
earth beagn in 1960s.
• Clutter studies
• SkYLab – radar altimeter and scatterometer in
1960s
• SEASAT in 1978
• ERS-1, JERS-1, ERS-2, RADARSAT, GEOSAT,
Topex-Posoidon
11/18/02
University of Kansas
Active Sensors – Radar Altimeter
• Radar altimeter is a short pulse radar
used for accurate height measurements.
– Ocean topography.
– Glacial ice topography
– Sea ice characteristics
• Classification and ice edge
• Vegetation
•http://topex-www.jpl.nasa.gov/technology/images/P38232.jpg
11/18/02
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Radar Altimeter
• Missions
Satellite Radar Altimeters
Mission
Frequency
Accuracy
SKYLAB
Ku
10 m
1973
GEOS
Ku
1-5 M
1976
SEASAT
Ku
~1 m
1978
GEOSAT
Ku
10 CM
1985-1990
ERS-1
Ku
< 10 cm
1992-1998
TOPEX
C &Ku
< 10 cm
1992-
ERS-2
Ku
< 10 cm
1996-
GFO
Ku
<10 cm
1998-
ENVISAT
Ku &S
<10 CM
2001-
Jason-1
Ku &C
<10 cm
2000-
CRYOSAT and other
missions
Ku
Few cm
2003-
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University of Kansas
Period
Radar Altimeter— Waveform
• Satellite altimeters operate
in pulse-limited mode.
R2  H 2  Y 2
c
RH
2
H
c 

2
2
H    H Y
2 

c
 H
2
c
H 2  cH  ( ) 2  H 2  Y 2
2
Y  cH
2
Ct/2
Amplitude
R  Re solution  2Y  2 cH
For H  800 km,  3.3 ns
R  1.7 km
Time
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University of Kansas
Radar Altimeter
• A short pulse radar
– Uses pulse compression to obtain fine range
resolution or height measurement.
– Range measurement uncertainty of a pulse radar.
r  
c
S
2B 2
N
For example B  300 MHz, S/N  100
r  3.5 cm
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University of Kansas
Radar altimeter
•
Other sources of errors
–
–
–
–
–
–
Atmospheric delays
Troposheric delays.
EM bias
Pointing errors
Orbit errors
Accuracies of few cms are
being achieved with new
generation sensors.
•
•
•
•
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Dual-frequency
Water vapor—
radiometers
GPS – orbit determination
Calibration.
Resti et al, “The Envisat Altimeter System RA-2,”ESA
Bulletin 98, June 1999
sigma=5.5 cm
University of Kansas
Radar Altimeter—typical system
Resti et al, “The Envisat Altimeter System RA-2,”ESA Bulletin 98, June 1999
11/18/02
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Radar Altimeter
• Waveform analysis
– Time delay is measured
very accurately and
converted into
distance.
– Spreading of the pulse
is related to SWH.
– Scattering coefficient
can be obtained by
determining the power.
Resti et al, “The Envisat Altimeter System
RA-2,”ESA Bulletin 98, June 1999
11/18/02
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Radar Altimeter- typical system
• Block diagram of Envisat RA
Resti et al, “The Envisat Altimeter System RA-2,”ESA Bulletin 98, June 1999
11/18/02
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Active sensors
• Scatterometer
– Scatter o Meter – A calibrated radar used to
measure scattering coefficient.
– They are used to measure radar backscatter as a
function of incidence angle.
– Ground and aircraft-based scatterometers are
widely used.
– Experimental data on variety of targets to support model
and algorithm development activities.
» Developing algorithms for extracting target
characteristics from data.
» Understanding the physics of scattering to develop
empirical or theoretical models.
» Developing target classification algorithms
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Active sensors— Scatterometers
• Wide range of applications
–
–
–
–
–
Wind vector measurements
Sea and glacial ice
Snow extent.
Vegetation mapping
Soil moisture
• Semi-arid or dry areas.
11/18/02
University of Kansas
Microwave Remote Sensing— Atmosphere
and Precipitation
• Global precipitation mission
– Will consist of a primary spacecraft and a
constellation.
• Primary Spacecraft
– Dual-frequency radar.
» 14 and 35 GHz.
– Passive Microwave Radiometer
– Constellation Spacecraft
• Passive Microwave Radiometer
11/18/02
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Microwave Remote Sensing—Active
Sensors
Imaging Radars
Imaging Radars & Scatterometers
• Imaging Radars
• Real Aperture Radar (RAR)
• Synthetic Aperture Radar (SAR)
• Widely used for military and civilian
applications.
• RAR
• Thin long antenna mounted on the side of an
aircraft.
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Imaging radars
• RAR
• RAR geometry
– Resolution is
determined by
antenna beamwidth in
the along track
R
r  R  k
direction
D
a
a
k  weighting factor
– Pulse width in the
cross-track direction
rc 
11/18/02
c
2 sin(  )
University of Kansas
Imaging radars
•
•
For a radar operating
at f=10 GHz with a 3-m
long antenna in the
along track direction
and 0.5 us pulse,
resolution at 45 degree
incidence and range of
10 km is given by
Assume k=0.8
11/18/02
10000 x0.03
 80 m
3
3 x108 x0.5 x10 6
rc 
 106 m
2 sin( 45)
R  100 km
100000 x0.03
ra  0.8
 800 m
3
3 x108 x0.5 x10 6
rc 
 106 m
2 sin( 45)
ra  0.8
University of Kansas
Imaging Radars: RAR
RARs were used
until 1990s.
They are replaced
by SARs.
Resolution should
1/20 about the
dimensions of the
target we want to
recognize
• Resolution
MRS: vol. II, Ulaby, Moore and Fung
11/18/02
University of Kansas
SAR
• Synthetic Aperture Radar
•
•
Use the forward motion of an aircraft or a
spacecraft to synthesize a long antenna.
Satellite SARs
•
•
11/18/02
ERS-1, ERS-2, RADARSAT, ENVISAT, JERS-1,
SEASAT, SIR-A,B& C.
Applications
•
•
•
•
•
•
Ocean wave imaging
Oil slick monitoring
Sea ice classification and dynamics
Soil moisture
Vegetation
Glacial ice surface velocity
University of Kansas
SAR
• We can use a small physical antenna
• For focused SAR resolution is
independent of
• Wavelength
• Range
• Best possible resolution is L/2
• Where L= length of the physical antenna
11/18/02
University of Kansas
RF Spectrum
Microwave Radiometry covers a range of frequencies.
Soil
Moisture
1-3 GHz
Resolution /
aperture


30 cm
3 cm
1 GHz
10 GHz
Sea Surface Salinity
1-3 GHz
Receiver sensitivity/
stability
Atmospheric
Water Vapor
22, 24, 92, 150,
183 GHz
Accuracy
Atmospheric
Temperature
54, 118 GHz
Accuracy
Ocean Surface Wind
19, 22 GHz
Polarimetry
Cloud Ice
325, 448, 643 GHz
High frequency
0.3 mm
3 mm
Atmospheric
Chemistry
190, 240, 640,
2500 GHz
High frequency
Precipitation
11, 31,37,89 GHz
Frequent global
coverage
Sea Ice
37 GHz
Polar coverage
1000 GHz
100 GHz
Hartley, NASA
L band
11/18/02
S band
C band
X band
Ku/K/Ka band
University of Kansas
Millimeter
Submillimeter
Microwave Radiometers— theory
• Planck’s Law of radiation
s ( , T ) 
2hc 2

1
5
e
ch
kT
1
• Where S(λ,T) =Intensity of
radiation in w/m2
• T = temperature in Kelvins
• h = Planck’s constant, 6.625 ×
10-34 J·s
• c = velocity of propagation
m/s
• k = Boltzmann constant,
1.380 × 10-23 J/K
• λ = wavelength, m
11/18/02
University of Kansas
Rayleigh  Jeans Approx
ch
 kT

S ( , T ) 
2ckT
4
Microwave Radiometer
• At microwave frequencies radiation
intensity is directly proportional to the
temperature.
• For gray bodies
–
–
–
–
–
11/18/02
Pa = kTb B
k =Boltzman constant, B = bandwidth, Hz.
Tb = Brightness temperature, K
Tb =e Tphy
e = Emissivity of the object or media
University of Kansas
Microwave Radiometer
Two basic types of radiometers
– Total power radiometer
• Highest sensitivity
– Switching-type radiometers and its variants.
T 
• Typical total power radiometer
TTotal
B in
where Ttotal  Ta  Tsys
B bandwidth
Mixer
Square-law det
IF Amp
LNA
Bandpass Filter
Integrator
 in  int egration time
B  6 MHz , in  1s
Ttotal  500 K
 T  0 .2 K
Local Oscillator
11/18/02
University of Kansas
Microwave Radiometer
• Dicke or Switching-type radiometer
– Any fluctuations in gain of the receiver will
reduce radiometer sensitivity.
– To eliminate system effects, Dicke
developed switching type radiometer.
• It consists of switch and a synchronous
detector. The input is switched between the
antenna and noise source. If the injected noise
power is equal to input signal power, the effect
of gain fluctuations is eliminated.
11/18/02
University of Kansas
Microwave Radiometer
• Typical Dicke-type radiometer
Modulator
Bandpass Filter
Mixer
Diff Amp
+
LNA
IF Amp
L
+
Noise
source
Local Oscillator
If the duty cycle is 50%, integratio n time is reduced by 50%
1.4Ttotal
T 
B in
11/18/02
University of Kansas
RF Radiometry Characteristics
Moden Radiometer
Digital processor
To eliminate down conversion process
Antenna
Receiver
low noise
amplifier
mixer
multiplexer/
spectrometer
LO
scan
11/18/02
University of Kansas
detector/
digitizer
Hartley, NASA
digital
processor/
correlator
Microwave Remote Sensing
• Research and application of
microwave technology to remote
sensing of
– Oceans and ice
– Solid earth and Natural hazards..
– Atmosphere and precipitation.
– Vegetation and Soil moisture
11/18/02
University of Kansas
Microwave Remote Sensing— Ocean and
Ice
• Winds
– Scatterometer.
• Quickscat, Seawinds
– Polarimetric radiometer
• Ocean topography
– Radar altimeters
• Ocean salinity
– AQUARIUS
• Radiometer and radar combination.
– Radar to measure winds for correcting for the effect
of surface roughness.
11/18/02
University of Kansas
Ocean Vector Winds— Scatterometers
Scatterometers send microwave pulses to the
Earth's surface, and measure the power scattered
back. Backscattered power over the oceans
QuikScat
depends on the surface roughness, which in turn
SeaWinds
depends on wind speed and direction.
QuikScat
•
Replacement mission for NSCAT, following loss of ADEOS
•
Launch date: June 19, 1999
SeaWinds
•
EOS instrument flying on the Japanese ADEOS II Mission
•
Launch date: December 14, 2002 ????
Instrument Characteristics of QuikScat and SeaWinds
•
Instrument with 120 W peak (30% duty) transmitter at 13.4
GHz, 1 m near-circular antenna with two beams at 46o and 54o
incidence angles
Advanced sensors– larger aperture
antennas.Passive polarimetric sensors.
11/18/02
University of Kansas
Courtesy: Yunjin Kim, JPL
Ocean Topography Missions
The most effective measurement of ocean currents
from space is ocean topography, the height of the sea
surface above a surface of uniform gravity, the geoid.
TOPEX/Poseidon and Jason-1
•
Joint NASA-CNES Program
–
–
•
Instrument Characteristics
–
–
–
•
•
TOPEX/Poseidon launched on August 10, 1992
Jason-1 launched on December 7, 2001
Ku-band, C-band dual frequency altimeter
Microwave radiometer to measure water vapor
GPS, DORIS, and laser reflector for precise orbit determination
Sea-level measurement accuracy is 4.2 cm
TOPEX/Poseidon & Jason-1 tandem mission for high resolution ocean
topography measurements
The priority is to continue the measurement
with TOPEX/Poseidon accuracy
on a long-term basis for climate studies.
Courtesy: Yunjin Kim, JPL
11/18/02
University of Kansas
TOPEX/Poseidon Ocean topography
of the Pacific Ocean during El Niño
and La Niña.
Ocean Surface Topography Mission
An Experimental Wide-Swath Altimeter
By adding an interferometric radar system to a conventional radar altimeter
system, a swath of 200 km can be achieved, and eddies can be monitored over
most of the oceans every 10 days. The design of such a system has
progressed, funded by NASA’s Instrument Incubator Program. This
experiment is proposed to the next mission, OSTM (Ocean Surface
Topography Mission)
South America
Courtesy: Yunjin Kim, JPL
11/18/02
University of Kansas
Global Ocean Salinity
•
•
Aquarius (JPL, GSFC, CONAE)
•
ESSP-3 mission in the risk
mitigation phase
First instrument to measure global
ocean salinity
– Passive and active microwave
instrument at L-band
– Resolution
• Baseline 100km, Minimum
200km
– Global coverage in 8 days
–
–
1 week of salinity measurements from space
Accuracy: 0.2 psu
Baseline mission life: 3
years
11/18/02
Courtesy: Yunjin Kim,
University of Kansas
100 yrs of salinity measurements by ship
JPL
SRTM (Shuttle Radar Topography Mission)
•
•
•
•
•
• Partnership between NASA and NIMA
(National Imagery and Mapping Agency)
•X-band from German and Italian space
agencies
•
•
Courtesy: Yunjin Kim, JPL
11/18/02
C-band single pass interferometric SAR for
topographic measurements using a 60m
mast
DEM of 80% of the Earth’s surface in a
single 11 day shuttle flight
– 60 degrees north and 56 degrees south
latitude
– 57 degrees inclination
225 km swath
WGS84 ellipsoid datum
JPL/NASA will deliver all the processed data
to NIMA by January 2003
Absolute accuracy requirements
– 20 m horizontal
– 16 m vertical
The current best estimate of the SRTM
accuracy is
• 10 m horizontal and 8 m vertical
University of Kansas
L-band InSAR Technology
•
•
Interferometric Synthetic Aperture Radar
(InSAR) can measure surface
deformation (mm-cm scale) through
repeated observations of an area
• L-band is preferable due to longer
correlation time due to longer
wavelength (24cm)
Solid Earth Science Working Group
recommended that
• In the next 5 years, the new space
mission of highest priority for solidEarth science is a satellite
dedicated to InSAR measurements
of the land surface at L-band
11/18/02
Surface deformation due to Hector Mine
Earthquake using repeat-pass InSAR data
InSAR velocity difference indicates a 10%
increase in ice flow velocity from 1996 to
2000 on Pine Island Glacier
University of Kansas [Rignot et al., 2001]
Microwave Remote Sensing— Soil
Moisture.
Southern Great Plains Hydrology Experiment (SGP97)
Surface Soil Moisture Derived From Remotely Sensed Microwave Data
37.0
Radar
Pol: VV, HH & HV
Radiometer
Soil Moisture (%)
5050
ElReno
35.5
dT= 0.64º K
ElReno
OklahomaCity
Chickasha
OklahomaCity
4040
Chickasha
35.0
3030
July 2
July 3
Lamont
Lamont
36.5
SGP’97
2020
36.0
ElReno
OklahomaCity
ElReno
1010
OklahomaCity
Chickasha
Chickasha
35.0
-98.5
Res =40 km,
Lamont
36.0
35.5
Pol: H, V
July 1
Lamont
Latitude (Degrees)
Res – 3 and 10 km
June 30
36.5
00
-98.0
-97.5
-98.0
-97.5
-97.0
Longitude (Degrees)
NASA Land Surface Hydrology Program
Courtesy: Tom Jackson, USDA
• HRDROS
– Back-up ESSP mission for global soil moisture.
• L-band radiometer.
• L-band radar.
11/18/02
University of Kansas
Microwave Remote Sensing— Atmosphere and
Precipitation
CloudSAT
Salient Features
NASA ESSP mission
First 94 GHz radar space borne system
Co-manifested with CALIPSO on Delta launch vehicle
Flies Formation with the EOS Constellation
Current launch date: April 2004
Operational life: 2 years
Partnership with DoD (on-orbit ops), DoE
(validation) and CSA (radar development)
Science
Measure the vertical structure of clouds and quantify their ice and water content
Improve weather prediction and clarify climatic processes.
Improve cloud information from other satellite systems, in particular those of Aqua
Investigate the way aerosols affect clouds and precipitation
Investigate the utility of 94 GHz radar to observe and quantify precipitation, in the
context of cloud properties, from space
11/18/02
University of Kansas
Courtesy: Yunjin Kim, JPL
Earth Science and RF Radiometery
Atmospheric chemistry
Precipitation
Microwave
Radiometry
Sea surface temperature/
Sea surface salinity
Applications.
Hartley, NASA
Ocean surface wind
Atmospheric temperature, humidity, and clouds
11/18/02
University of Kansas
Soil moisture
Conclusions
• A brief overview of microwave remote
sensing principles and applications.
• Opportunities for research and
education.
– Science
– Technology
11/18/02
University of Kansas
SAR—Principle
• SAR can explained using the concept
of a matched filter or antenna array.
Ro
11/18/02
University of Kansas
SAR— Principle
• Unfocussed SAR
• No phase corrections are made.
o 
4Ro

4R
N 

2
l2
l
2
R  R0     Ro 
8Ro
 2
Ro
4l 2 
 d   N  o 

8Ro  4
r
l
11/18/02
University of Kansas
Ro 
2
SAR— Principle
• Focussed SAR

x2 
 x 2   Ro 1  2 
 Ro 
x2
R  Ro 
2 Ro
R
x
Ro
R
d ( x) 
0.5
2
o
2

2
x2
2x 2

2 Ro Ro
Thus we need to correct th e phase by to make all the vectors add up
11/18/02
University of Kansas
2x 2
Ro
SAR— Principle
• Resolution
The 3 - dB beamwidth of an uniformly illuminate d real
aperture of length, D, is given by  ar  0.88

D
For synthetic aperture of length, Leff ,  as  0.44

Lef
4 - dB beamwidth are given by
 ar 

D
,  as  0.5

Lef
& Lef 
Ro
D
Along track resolution , ra   as Ro 
11/18/02
Ro
2 Le f

D
2
University of Kansas