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KaRIn – the Ka-band Radar Interferometer on SWOT: Measurement Principle, Processing and Data Specificities
Roger Fjørtoft, Jean-Marc Gaudin, Nadine Pourthie, Christine Lion, Alain Mallet, Jean-Claude Souyris (CNES DCT/SI/AR)
Fifamè Koudogbo, Javier Duro, Patrick Ordoqui, Alain Arnaud (Altamira Information)
Christian Ruiz (CapGemini)
SWOTIGARSS 2010, Honolulu, Hawaii, 25-30 July 2010 2
Outline
■ Introduction Mission, satellite, KaRIn instrument
■Measurement principle Absolute vs. relative height restitution
■Processing LR (oceanography), HR (hydrology)
■Specificities of KaRIn images Ka-band, near-nadir
SWOTIGARSS 2010, Honolulu, Hawaii, 25-30 July 2010 3
Mission objectives and scientific requirements
■Mission SWOT (Surface Water and Ocean Topography) = innovative altimetry mission
improved spatiotemporal coverage for oceanography and high resolution altimetry data for hydrology.
KaRIn : Single pass Ka-band interferometric SAR system (JPL concept). Co-operation between NASA/JPL (USA) and CNES (France) Launch date: 2019 - 2020
■Main scientific requirements
Oceanography: Global coverage (<78°), sea surface height precision < 2 cm at ~1 km resolution LR mode
Hydrology: Global inventory of rivers > 100 m (50 m) and lakes > (250 m)2, height precision < 10 cm at average spacing 50 m, slope precision :1 cm/km HR mode
Introduction
SWOTIGARSS 2010, Honolulu, Hawaii, 25-30 July 2010 4
Xs
Ys Zs
■ Platform 1300 kg 1600W (orbit average) >21 m2 solar arrays High performance ACDS 4 Tb mass memory 655 Mbps X-Band TM
■ Payload (nominal configuration) Ka Band Radar Interferometer Ku/C Nadir Altimeter Water vapor radiometer POD suite: Doris + LRA + GPSP
SWOT satellite
Introduction
Preliminary figures fromthe CNES phase 0 study
10 m mast
■ Orbit 970 km 78° Non SSO 22 days repeat pass
SWOTIGARSS 2010, Honolulu, Hawaii, 25-30 July 2010 5
KaRIn
■ Ka-band Radar Interferometer : bistatic SAR (35.75 GHz 100 MHz)
■ 10 m mast
■ Near-nadir swaths (0.6-4.1°) on both sides of the track.
■ Monostatic mode improves the interferometric sensitivity by a factor of 2.
■ Intrinsic SAR resolution2 m x (70 – 10 m)
■ HR mode (hydrology): 4 m x (70 – 10 m)
■ LR mode (oceanography): 1 x 1 km2
■ Continuous acquisition
Vsat
(Altitude 970 km)
2 m70 – 10 m
20 km140 km
60km
60km
Introduction
SWOTIGARSS 2010, Honolulu, Hawaii, 25-30 July 2010 6
h
B
r
H
r1
r2
sin12 Brrr
2r
.2
arcsinB
cosrHh
Absolute height through SAR interferometry
B = horizontal baseline (mast length) = wavelengthH = satellite altitude (orbit)r1 = distance master antenna – target (time)
r2 = distance slave antenna – target (time) = unwrapped interferometric phase = incidence angle
’ = measured interferometric phase [0,2]
= n•2 + ’
n must be determined from auxiliary data
Measurement principle
A1 A2
P
SWOTIGARSS 2010, Honolulu, Hawaii, 25-30 July 2010 7
Challenges of absolute height restitution
■ KaRIn can restitute absolute height with auxiliary data : absolute height reference with accuracy within ± Ea/2 (Ea : altitude of ambiguity, ranging from 10 to 60 m)
Ocean (LR mode): mean sea surface and tide models, or nadir altimeter measurements
Hydrology (HR mode): DEM (SRTM or better)
■ Phase unwrapping on a pixel-by-pixel basis implies tropospheric correction throughout the swath.
■ Alternative solution: Phase unwrapping from reference points (e.g. DEM, similar to conventional SAR interferometry) tropospheric correction should no longer be necessary (current baseline for HR processing).
Measurement principle
SWOTIGARSS 2010, Honolulu, Hawaii, 25-30 July 2010 8
Processing steps
■SAR processing (range and azimuth compression)
■ Interferometric processing (co-registration, computation of interferometric phase and coherence)
■Restitution of “acquisition geometry” (geolocation, precise orbit determination, correction of roll, baseline variations, tropospheric delay, …)
■Extraction of geophysical parameters (water surface detection (HR only), computation of water surface heights, slopes etc.)
■Multitemporal analysis (medium and long term variations: flooding, floodplains, …)
Processing
SWOTIGARSS 2010, Honolulu, Hawaii, 25-30 July 2010 9
■ LR mode (oceanography) Unfocussed SAR processing Interferometric processing (including co-registration) Averaging/multilooking ( 1 km resolution) BAQ coding, transmission, decoding, reformatting Geolocation Calibration (roll and baseline variations, tropospheric corrections) Absolute height restitution SSH Estimation of SWH and wind speed, SSH slopes, 0
Resampling of all products to geographically fixed grid (1 km)
■ HR mode (hydrology) Pre-summation by factor 2 in azimuth direction BAQ coding, transmission and decoding, reformatting SAR processing Interferometric processing (including co-registration) Geolocation Detection of water surfaces (prior information slant range) Phase unwrapping/flattening, fit to existing DEM (calibration) Adaptive averaging within water bodies absolute heights, slopes etc. Resampling to triangular irregular network (TIN), 50 m average spacing Multitemporal analysis (on fixed grid)
Processing steps (preliminary)
Onboard processing
Ground processing
Onboard processing
Ground processing
> 1 Gb/s
0.2 Mb/s
> 1 Gb/s
300 Mb/s
Processing
SWOTIGARSS 2010, Honolulu, Hawaii, 25-30 July 2010 10
Unfocussed SAR processing
Reference: Full SAR processing + multilooking to ~100 m resolution
(Simulated SAR image based on DEM)
Unfocussed processing (LR mode)~100 m resolution + multilooking
(Barely visible degradation)
Unfocussed processing (burst mode)
(Clearly visible loss of details)
Processing
SWOTIGARSS 2010, Honolulu, Hawaii, 25-30 July 2010 11
Unfocussed SAR processing Assessment of impact on interferograms
Full SAR processing (reference)
Unfocussed processing (LR mode)
After further multilooking to the 1 km2 grid, the loss in height precision w.r.t. full SAR processing is about 1 mm (not yet optimized).
Unfocussed processing (burst mode)
Processing
SWOTIGARSS 2010, Honolulu, Hawaii, 25-30 July 2010 12
■Sub-optimal performance with simple methods due to speckle (and possibly limited water/land contrast)
Pixelwise K-Means, ML, SVM, …
■Spatial context and available prior data must be exploited
■Assessment of advanced methods : Active contours / snakes (update water surface boundaries starting
from existing mask) Narrow structure extraction (cf. road detection in SAR images) Markov chain and Markov random field classification methods Hybrid segmentation : edge detection, region merging, edge position
refinement …
Processing
Detection of water surfaces
SWOTIGARSS 2010, Honolulu, Hawaii, 25-30 July 2010 13
… w.r.t. existing spaceborne earth observation SAR systems
■ Ka-band (wavelength of only 8.6 mm) [compared to X-, C-, L-band] Less specular reflection Weaker penetration into vegetation, soil, snow,… Higher sensitivity to tropospheric conditions & rain A smaller baseline can be used for interferometry (10 m mast) Few reports on backscattering from natural surfaces, especially in
■ Near nadir (0.6-4.1° incidence) [typically 20-50° for spaceborne SAR] Strong layover Inversion of land/water radiometric contrast w.r.t. SAR (water > land) Strong relative incidence variation, implying strong/rapid range variation in
several key parameters (pixel size, altitude of ambiguity, orbital fringes, …)
■ R. Fjørtoft et al., “Specificities of Near-nadir Ka-band Interferometric SAR Imagery”, Proc. EUSAR 2010.
Specificities of KaRIn data
SWOTIGARSS 2010, Honolulu, Hawaii, 25-30 July 2010 14SAR images Coherence Interferogram
Simulation of SLC images
■ Radiometric simulator: Simulation of RCS for different surface types in various conditions (sensitivity studies, case studies)
Bare soil [Hybrid IEM-GO + Hallikainen/Dobson] Water surfaces [Hybrid IEM-GO + Meissner/Wentz] Vegetation (trees) [Rad. transf.+ Ulaby/El-Rayes] …
■ Geometric simulator Integrates results of radiometric simulator Geometric effects such as layover, shadow etc. Simulation of interferometric pairs of SLC images
DEMLand cover classes
EM models
Orbit file
a
r
Layover/ shadow mask
Studies of detection of water surfaces, absolute height restitution, …
Simulation
SWOTIGARSS 2010, Honolulu, Hawaii, 25-30 July 2010 15
Simulation of raw images
Simulation
ΔT = t0 – t
-1 = t
+1 – t
o = 1 / PRF
→V
t-1
to
t+1
RCSt-1
RCSto
RCSt+1
Stacking of all “raw images”
indexed by time
Focussing
Final RAW image
level 1 data
Study impact of moving water
SWOTIGARSS 2010, Honolulu, Hawaii, 25-30 July 2010 16
■ SWOT = NASA / JPL – CNES cooperation
■ Measurement principle (JPL concept) Ka-band near-nadir interferometric SAR (bistatic/monostatic, two swaths) Absolute height restitution in LR mode, relative in HR mode (current baseline)
■ Processing Onboard unfocussed SAR and interferometric processing in LR mode Automatic detection of water surfaces in HR mode
■ Specificities of Ka-band interferometric SAR
Few quantitative reports on Ka-band backscattering from natural surfaces Severe layover distortion (terrain slope often greater than look angle) Strong relative incidence angle variation, implying strong/rapid variation in several
parameters: range pixel size, altitude of ambiguity, orbital fringes, …
■ Outlook Extension of simulation activities Ground measurements and airborne campaigns Prototyping of processing chains
Summary and outlook
SWOTIGARSS 2010, Honolulu, Hawaii, 25-30 July 2010 17Thank you for your attention