cours sar part2

1 Télédétection radar – 3A SICOM SIM SN

INSIS Fundamentals of Remote Sensing: SAR Interferometry

Notions fondamentales de télédétection : l’interférométrie RSO

Gabriel VASILE Chargé de Recherche CNRS

[email protected]


Range focusing

Azimuth focusing

range

azim

ut

SAR amplitude image ©SYTER, Telecom ParisTech

SAR focusing: ERS-1, Chamonix valley, 512 × 512 pixels


Range focusing

Azimuth focusing

azim

ut

range

SAR focusing: ERS-1, Chamonix valley, 512 × 512 pixels

SAR phase image ©SYTER, Telecom ParisTech


Emission: H and V Reception: H and V

Penetration depth

Backscattering mechanisms

+

Propagation

2 phenomena -> differential measurements

Sinclair formula & differential measurements


Two SLC images: kM (master), kS (slave) Same target area Slightly different viewing angles Hermitian product -> complex cross-correlation

Internal coherence M&S intensities

Differential measurements – InSAR


Two SLC images: kM (master), kS (slave) Same target area Slightly different viewing angles Hermitian product -> complex cross-correlation

Normalized complex cross-correlation

INTERFEROMETRIC PHASE: φ = arg{C} INTERFEROMETRIC COHERENCE: c = ABS{C}

Differential measurements – InSAR


Fully polarimetric SAR data Cross-polar symmetrisation (monostatic case)

Vectorisation on the Pauli basis (target vector): k=[SHH+SVV SHH-SVV 2SHV]T

Hermitian product -> complex correlation Polarimetric coherency matrix

Differential measurements – POLSAR


Polarimetric interferometric coherency matrix:

Polarimetric M&S coherency matrices:

Differential measurements – POL-InSAR


Radar Interferometry Outlines

Overview of interferometry Satellite Interferometry Satellite InSAR geometry InSAR processing

measuring topography Satellite Differential InSAR D-InSAR processing

measuring motion on the Earth’s surface SAR examples


Satellite Interferometry

For satellite interferometry of the repeat-pass type, one image is taken one day, and a second image is taken of the same scene one or more days later. More images can be taken at later intervals and used in the processing,

as long as the scene retains reasonable coherence over the longer time interval

Because there is always a time delay, and usually parallax as well, assumptions must be made or processing must be done to remove the unwanted component of motion or topography

In Feb. 2000, the Shuttle Radar Topography Mission obtained topographic (elevation) data of much of the Earth’s surface using single-pass interferometry, i.e., image pairs were acquired at the same time using two radar antennas separated physically to create a 60-m fixed baseline.


Radar Interferometry from Space

SRTM

TANDEM ERS-1/2



SRTM

TANDEM ERS-1/2


Radar Interferometry from Space : SRTM mission

NASA / DLR


Coverage of 11-day SRTM Mission (Feb. 2000)

NASA / DLR


SRTM Perspective View with Landsat Overlay

NASA / DLR

Elevation data from C-band across-track interferometric radar, SRTM Acquired Feb. 16, 2000 Height exaggeration 2x Landsat overlay Acquired: Dec. 14, 1984 View toward the North 34.42°N 119.17°W

Santa Clara River Valley, California


ERS –1 and ERS – 2 TANDEM Mission (1995-2000)

ESA • Repeat pass interferometric SAR uses two antenna positions to acquire two SAR images.

• Vertical height is determined by comparing phase measurements.

• Observable terrain shifts are on the order of the radar wavelength or smaller.




ERS –1 and ERS – 2 TANDEM Mission • Colour: Interferogram Phase, 16

steps from 0 to 2π radians • Intensity: Interferogram Magnitude • Saturation: Coherence • Interferogram Magnitude is the

background black-and-white image - similar to regular SAR image.

• Coherence (colour brightness) indicates the degree of phase correlation. Low coherence indicates greater change (lakes at upper left). High coherence indicates least change (exposed rocks at lower left).

• Colour-coded interferogram phase: a phase change of 2π radians corresponds to an altitude change of 232 m

Schefferville, Québec


Satellite Repeat-pass InSAR Geometry

• A radar is essentially a distance or range measuring sensor

• It can measure range in 2 ways: • Time delay:

R=c/2B = 8 m • Phase:

R=λ/100 = 1 mm • Phase is much more accurate • but is a relative measurement only


How a SAR Measures Phase


Phase after Scattering from a Random Surface


Interferometer Phase


How Differential Phase Measures Topography


Interferometric phase ambiguity

Wrapped phase φ = φ (mod 2π)

Nyquist criterion | φ(N) − φ(M)| < π

Unwrapped phase φ

φ

“Automatic’’ methods: local approach : cuts positioning, propagation global approach: least squares (phase or local frequencies)

Phase Unwrapping

€

φc (M,N) =

φ(N) −φ(M) if φ(N) −φ(M) < π

+2π if φ(N) −φ(M) ≤ −π−2π if φ(N) −φ(M) ≥ π

⎡

⎣

⎢ ⎢ ⎢

⎤

⎦

⎥ ⎥ ⎥


2 images single look complex (SLC):

After co-registration:

Complex multi-looking: (m,n) (i,j)

SLC 1

Coh. Phase

Amp 1 Amp 2

SLC 2

Interferogram Estimation


Distribution of the sample coherence d as function of theoretical coherence value D and the number of looks L>1:

Distribution function of L, D = 0.5 Bias function of L

Coherence Estimation


Distribution of the sample phase φ as function of theoretical coherence value D and the number of looks L>1:

Distribution function of D β = 0, L = 4

Distribution function of L β = 0, D = 0.7

D

Phase Estimation


Measuring Coherence

Coherence must always be measured to assess the suitability of the data set for InSAR processing

Coherence magnitude is closely related to the local standard deviation of differential phase

High coherence magnitude tells us: images have good SNR phase centres of scatterers are stable any motion is spatially “organized”

Coherence magnitude: 0.3 - 0.5 is useable, but noisy 0.5 - 0.7 is good 0.7 - 1.0 is excellent

Coherence has also been successfully used as a terrain classification parameter: water, vegetation, desert, city


InSAR Processing

Process data to SLC images Register the two images to 1/10 pixel Over-sample by a factor of 2 in both dimensions Filter common bands in spectrum Conjugate multiply to form interferogram Smooth the interferogram Measure coherence Unwrap phase Estimate geometry parameters (especially baseline) Remove flat-earth fringes Convert unwrapped phase to height and/or motion


InSAR Processing: Chitina River Valley, S.E. Alaska

ERS images acquired Feb. 1994

• B⊥ = 40 m • Flat-earth fringes were

removed. • Phase is still wrapped. • Each revolution of the colour

wheel represents an increase of 200 m in altitude.


Topography Contours from Interferogram: ERS-1, 1991

Franklin Bluffs and Sagavanirktok River on the North Slope of Alaska Perspective view generated from an interferometrically derived DEM


Radar Differential Interferometry from Space



The information contained in the D-InSAR phase can be decomposed in:




D-InSAR: orbital compensation


D-InSAR: topographic compensation (DTM)


D-InSAR: adaptive filtering

38 Télédétection radar – 3A SICOM SIM SN LISTIC/LAPI 38

Glaciology: temperate glaciers Location

French Alps – “Chamonix Mont-Blanc” test site

Mer-de-Glace Argentière Location 45°55’15’’ N/ 6°55’45’’ E 45°56’15’’’N / 7°00’30’’ E

Area / Length 3,5 (km²) / 4.7 (km) 15 (km²) / 9 (km)

Mean slope ~ 9° (17%) ~14° (26%)


ERS ascending (image panchromatic SPOT-1) ERS descending

ERS - 1/2: visibility assessment


ERS-1/2 Interferogram (March 1996)

TANDEM ERS (Mer-de-glace)

(c) 100 km

5 km

SAR amplitude

InSAR coherence InSAR phase


Mer-de-glace [660 × 361 pixels]

amplitude coherence phase

IDAN ML amplitude IDAN ML coherence IDAN ML phase


Measuring Glacier Velocity by D-InSAR

filtered coherence

filtered phase

2D local frequencies

mesures In situ DTM

velocity field

TANDEM ERS, 10/11-March-1996 Chamonix Mont-Blanc


IDAN ML unwrapped phase IDAN ML phase mod 2π

Mer-de-glace [618 × 405 pixels]: weighted least-square phase unwrapping


From Slant Range to Ground Range DTM (Lat/Lon, WGS 1984):

separating relief / displacement geocoding

D-InSAR scalar measurement: slant range displacement


Glacier Velocity Field: Argentière & Mer-de-glace “In situ” measurements:

unknown offset ablation sticks differential GPS

D-InSAR/DTM measurements: 3D displacement field glacier flow direction (SPF,MSF)


55 Télédétection radar – 3A SICOM SIM SN 55

TerraSAR-X StripMap Acquisition (3m res) of the Pyramids of Giza, Egypt Prel. Image recorded during calibration phase


" South Nigeria, 3m res

TerraSAR-X Basic Image Products

City of Warri

Warri airport



" Cape Town (South Africa) – 1m res

International airport



Mombasa (Kenya) – 1m res



" Addis Abeba (Ethiopia), 3m res


Bibliography

H. Maître, Traitement des images de RSO, Hermes Sciences Publications, 2001

L. Lliboutry, Sciences Géométriques et Télédétection, Masson, 1992 C. Elachi, Introduction to the Physics and Techniques of Remote Sensing,

Wiley Series in Remote Sensing, 1987 Tutoriel du Centre Canadien de Télédétection (CCT):

http://www.ccrs.nrcan.gc.ca/resource/index_f.php#tutor Trouvé E., Imagerie Radar à Synthèse d’Ouverture, cours ETASM,

Université de Savoie, 2004 Faller N., TerraSAR-X: Surveying, Mapping & Infrastructure Development,

Map Africa 2007 Hajnsek I. at al., TerraSAR-X Mission: Application and Data Access,

Int. Summer School on Very High Resolution Remote Sensing, 2009

cours sar part2

Documents

nasa dlr

target area

basic image

differential

radar differential

radar interferometry

sar focusing

satellite