The document discusses Synthetic Aperture Radar (SAR) interferometry, detailing the processes involved in creating interferograms, phase unwrapping, and height conversion using phase differences from two SAR images. It outlines error sources like baseline accuracy and coherence levels that impact measurement accuracy. Additionally, it highlights applications of SAR data in geological surveys and monitoring deformation and other changes in the landscape.

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SAR INTERFEROMETY

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Concept of Interferomety
Young’s Double slit experiment

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SAR Interferomety

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Methods for SAR Interferomety

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Fig(3.5) SAR Geometry and various components of Interferometric pair

6. B
A1
A 2
• Two images of the same area
are required, measured from
slightly different positions (A1
and A2)
•Due to the range difference d
coming phases are out. These
phase differences contain height
information of the surface point
and are used to create the
interferograms
q


’
h
z(x,y)
y
z
a
d
Insar Geometry

7. h
r
r-r’
r-r’ = range difference (red)
Number of waves can be
retrieved from the
interferogram after phase
unwrapping r’
Phase difference
Df = ( r -r’) 2p/l mod(2p)
Phase Difference

8. [Number of waves]
r-r’ [Meters]
l
Phase Difference

9. Data Format
SLC = Single Look Complex
Every resolution element contains
- Magnitude
- Phase ( between 0 and 2p radians) of
backscattered signal
Phase
0
180
360
Magnitude

10. One color cycle (fringe)
Equal to half of the
wavelength of the radar
wave, i.e. for ERS C
band SAR, 56 mm /
2=28 mm)
So by counting all the color
cycles we know how many
wavelengths fit inside r-r’
Phase differences

11. Data set 1
Phase Unwrapping
Image Co Registration
Data set 2
Interferogram Generation
Phase To Height
Conversion
Geocoding
InSAR Processing Flowchart

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• Visual interpretation of phase “images”of one
SAR image does not give any information
• Phase differences between corresponding
elements of two images can contain a
pattern (fringes)
Phase plot of one
SAR image contains
no useful information

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(a) Raw Interferogram (b) Filtered Interferogram
(c) Filtered and Flattened Differential
Interferogram
Interferometry with nearly zero baseline

14. COHERENCE MAP
ERS-1 ERS-2
The values in a
coherence map
are an indication
of the local
differences
between two radar
images.
Coherence map

15. Phase unwrapping
 Interferometric system does not measure the total pixel phase
difference. Rather, it measures only the phase difference that
remains after subtracting all full 2 intervals present (modulo
2). It is called a wrapped phase and has to be unwrapped or
calculated back to its real values.
 Unwrapped phase difference is used to calculate height.

16. Phase unwrapping
Phase difference as measured by interferometric system is as follows

17. Phase unwrapping

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Phase Unwrapping

19. Error Sources
• Baseline accuracy (horizontal and vertical) - orbits geometry
• Low Coherence (Phase Correlation) between the two SAR
images is the most important limitation and error source
• Decorrelation (loss of coherence) can be due to:
- Registration errors {spatial and spectral(e.g. c & x)}
- Temporal de-correlation
- Baseline de-correlation
- Orbit errors
- Inhomogeneous Atmosphere
- De-correlation has a direct effect on the interferometric
phase and thus on the height

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Non-Interferometric SAR Data Interferometric Pair

21. Raw SAR
Data
Coregistered Image
Interferogram
Phase Image
Flattened Interferogram
Differential Interferogram Geocoded Differential Interferogram
STEPS of SAR INTERFEROMETRY
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AVAILABLE
Sentinel-1A Data
ENVISAT Data
ALOS PALSAR Data
Satellite Sensor
ALOS-1 PALSAR
Mode Ascending
Polarisation HH, HV
Band L(=23cm)
Satellite Sensor
ENVISAT ASAR
Mode Descending
Polarisation HH
Band C(=5.6cm)
Satellite Sensor
Sentinel-1 C-SAR
Mode Descending
Polarisation HH,VV, HV,VH
Band C(=3.5-7.5cm)
Advanced Land Observation Satellite(ALOS)
Phased Array-type L-band SAR(PALSAR)

25. APPLICATION AREAS
• Digital elevation mapping
– Slopemaps (e.g. landslide hazards)
– DEM’s
• Deformation mapping
– Crustal motion
– Monitoring
• Use of temporal coherence information
– Classification
– Change detection

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