FR4.L09 - KARIN – THE KA-BAND RADAR INTERFEROMETER ON SWOT: MEASUREMENT PRINCIPLE, PROCESSING AND...
Transcript of FR4.L09 - KARIN – THE KA-BAND RADAR INTERFEROMETER ON SWOT: MEASUREMENT PRINCIPLE, PROCESSING AND...
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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)
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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
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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
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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
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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
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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
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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
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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
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■ 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
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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
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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
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■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
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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
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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
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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
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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
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SWOTIGARSS 2010, Honolulu, Hawaii, 25-30 July 2010 17Thank you for your attention