1. Introduction to SAR Imaging
Presenter: Chris Stewart, RSAC c/o ESA
Authors: Michael Eineder, Richard Bamler
Remote Sensing Technology (TUM/DLR)

2. Educational Objective
Understand the SAR imaging process and SAR instrument operation modes
Understand the relevant parameters of SAR systems
Understand the basic SAR scattering process
Understand the properties of SAR images
Know some SAR satellites and their main properties

3. Further Reading
Curlander, J. C., & McDonough, R. N. (1991). Synthetic Aperture Radar: Systems and Signal Processing. Wiley Series in Remote Sensing. New York: John Wiley & Sons, Inc.
Cumming, I. G., & Wong, F. H. (2005). Digital Processing of Synthetic Aperture Radar Data: Algorithms and Implementation. Boston, London: Artech House.

4. Structure Introduction Radar imaging (range-component)
Formation of synthetic aperture (azimuth-component)
Advanced SAR imaging modes
Characteristics of SAR images

5. Structure Introduction Radar imaging (range-component)
Formation of synthetic aperture (azimuth-component)
Advanced SAR imaging modes
Characteristics of SAR images

6. Airborne (DLR E-SAR) X-band SAR image 1 m resolution
The image shows some scattering phenomena: B/W, smooth runways, bright buildings (steel, corners), fields and forest with different roughness and dielectric constants
© DLR

7. Synthetic Aperture Radar - SAR
Active Þ independent of sun illumination
microwave Þ penetrates clouds and (partially) soil, snow wavelengths: X-band: 3 cm C-band: 6 cm L-band: 24 cm
coherent Þ interferometry, speckle
polarization can be exploited
spatial resolution: space-borne: 1 m m air-borne: > 0.2 m
Synthetic Aperture Radar (SAR)

8. SAR Imaging Geometry radar Radar transmits pulses and receives echoes
at the rate of the pulse repetition frequency:
PRF @ Hz
range:
radar principle =
scanning at speed of light
(slant) range
azimuth:
scanning in flight direction at
plus aperture synthesis
(holography)
coherent imaging:
complex-valued pixels
contain amplitude (brightness)
and phase information
azimuth
swath width
for this lecture: straight flight path
Fig.: © DLR
ground range

9. SAR – A Two-Step Imaging Process
SAR is a two-step imaging process:
1. Data acquisition Illumination of a scattering object and collection of received echoes Þ raw data Contribution of a single point is dispersed over 104 … 107 samples
2. Processing Raw data focusing Þ image of the object

10. SAR Image Examples Sensor: ERS-1 Mojave Desert CA, USA
azimuth
range
Sensor: ERS-1
Mojave Desert
CA, USA
Size » 40 km x 40 km
ERS-1 © ESA

11. SAR Raw Data (After Range Compression)
azimuth
ERS-1 © ESA

12. Focussed SAR Data
azimuth
ERS-1 © ESA
range

13. Focussed SAR Data after azimuth pixel averaging by 4
ERS-1 © ESA
after
azimuth pixel averaging by 4
to achieve approximately
square pixels

14. Structure Introduction Radar imaging (range-component)
Formation of synthetic aperture (azimuth-component)
Advanced SAR imaging modes
Characteristics of SAR images

15. Advanced SAR Modes: e.g. TerraSAR-X
ScanSAR (100 km swath, 15 m res.)
Stripmap (30 km swath, 3 m res.)
Azimut
Range
Spotlight (5 km swath, 1 m res.)
Point target response
Fig.: © DLR

16. ScanSAR (100 km swath, 15 m res.)
ScanSAR Mode
ScanSAR (100 km swath, 15 m res.)
Periodic switching of antenna elevation look direction:
Illuminate/receive only part (e.g. ¼) of synthetic aperture with bursts
Use remaining time to look („Scan“) at other ranges by steering the antenna electronically
 + increased swath width (e.g. × 4)
 - reduced resolution (e.g. ÷ 4)
Fig.: © DLR

17. Spotlight (5 km swath, 1 m res.)
Spotlight Mode
Spotlight (5 km swath, 1 m res.)
Increase aperture time by steering the antenna electronically backward in azimuth  longer illumination time, longer chirp
Higher chirp frequencies & aliasing with PRF need special processing techniques
 + increased resolution (e.g. × 3)
 - continuous operation not possible, limited azimuth image size (e.g. 5 km)
Fig.: © DLR

18. TOPS Mode (e.g. Sentinel-1)
TOPS (5 km swath, 1 m res.)
Reduce aperture time by steering the antenna electronically forward in azimuth
More azimuth distance, less illumination time per target
Saved time can be used to electronically steer the antenna to other elevation directions
 + increased swath width (e.g. S1: 3x = 250 km)
 - reduced resolution (e.g. S1: 17 m)
Fig.: © DLR

19. Structure Introduction Radar imaging (range-component)
Formation of synthetic aperture (azimuth-component)
Advanced SAR imaging modes
Characteristics of SAR images

20. SAR Image Characteristics
azimuth
range
Issues:
Resolution (shape of point scatterer response)
Radiometry
Geometry
Moving objects
Polarimetry
Artifacts
ERS-1 © ESA

21. Speckle “Noise”
Fig.: © DLR
ERS © ESA
Random positive and negative interference of wave contributions from
the many individual scatterers within one resolution cell
Varying brightness from pixel to pixel even for constant σ0
Granular appearance even of homogenous surfaces

22. Example for Bayesian Speckle Reduction
© AeroSensing GmbH
© AeroSensing GmbH
original SAR image
SAR data © AeroSensing GmbH
speckle filtered
Bayesian algorithm

23. Speckle Reduction by Temporal Multilooking (ERS)
+10dB
Data: ERS ©ESA
Data: ERS ©ESA/DLR
-10dB
5 spatial looks
20 x 20 m ground resolution
2 dB radiometric resolution
320 spatio-temporal looks
20 x 20 m ground resolution
0.3 dB radiometric resolution
Further Examples: Module Speckle Filtering

24. Parameters Influencing Radar Brightness
Sensor Parameters
wavelength (e.g. penetration through canopy)
polarization
look angle
resolution (texture)
Scene Parameters
surface roughness (e.g. Bragg scattering at ocean surfaces)
local slope and orientation Ü geomorphology
scatterer density, e.g. biomass, leaf density
3-D distribution of scatterers and scattering mechanism, e.g. surface, volume, or double bounce (canopy, trunks, buildings)
dielectric constant e Ü scattering material soil moisture vegetation status

25. Calibration of SAR Systems
Instrument parameters to be calibrated:
transmit power
receiver gain
elevation antenna pattern (satellite roll angle !)
Calibration objects:
corner reflectors
active radar calibrators (ARCs)
rain forest

26. Corner Reflectors for SAR End-to-End Calibration
Radar cross section of
a trihedral corner reflector: L
© DLR L
© DLR

27. strip 12 strip 03 strip 11 Radiometric Product Accuracy
Rainforest Stripmap VV
=20°-41°
strip 12
Radar brightness:
b0 = k * pixel-amplitude2 (k=calibration constant)
strip 03
Sigma nought from local incidence angle x,y
σ0 = b0 * sin(x,y )
strip 11
Application specific calibration assuming isotropic volume scattering
g0 = b0 * tan( x,y )
© DLR

28. Heavy Clouds and Rain Cells in X-Band SAR Images
 Only visible at short wavelengths and extreme conditions

29. Penetration of Microwaves
X-Band
λ=3 cm
C-Band λ=6 cm
L-Band λ=23 cm X C L
vegetation
dry soil
glacier ice
Fig.: © DLR

30. Scattering Mechanisms in Forests2 4 1 3 5
1: direct single scatter
2: multiple bounce
3: direct ground reflection
4: double bounce trunk - ground
5: attentuation of ground scatter by canopy
Fig.: © DLR

31. Geometry of SAR Images - Foreshortening
range
slant range
foreshortening
ground range
 Slopes oriented to the SAR appear compressed
ERS-1 © ESA
Fig.: © DLR

32. Geometry of SAR Images - Lay-over
range
lay-over
 Steep slopes oriented to the SAR lead to ghost images
ERS-1 © ESA
Fig.: © DLR

33. Lay-Over Mask Computed from DEM
© DLR
© DLR
100m DEM
simulated ERS-Image
white: lay-over

34. Geometry of SAR Images - Shadow
radar shadow
 Steep slopes oriented away from the SAR return no signal
Fig.: © DLR
azimuth
range
SRTM/X-SAR
SRTM© DLR

35. SAR-EDU – SAR Remote Sensing Educational Initiative