IGARSS11_FFBP_CSAR_v3.ppt

IGARSS 2011, Vancouver [email protected]

Octavio Ponce, Pau Prats, Marc Rodriguez-Cassola, Rolf Scheiber, Andreas Reigber

Microwave and Radar Institute (HR)

German Aerospace Center

Processing of Circular SAR TrajectoriesProcessing of Circular SAR Trajectorieswith Fast Factorized Back-Projectionwith Fast Factorized Back-Projection

July 28th, 2011Microwaves and Radar Institute Slide 2

Outline

Circular SAR (CSAR)

Fast Factorized Back Projection (FFBP)

FFBP for Circular SAR

Experimental Results

Conclusions


Acquisition Geometry

.

h

x

y

z

R


2D Sinc

Resolution – Stripmap 2D IRF

Kx

Kr

r

az

y

xTime Domain Frequency Domain


Resolution – CSAR 2D IRFy

xTime Domain

y Kx

Ky

x

Frequency Domain

Soumekh et al, IEEE TIP, 1996


Resolution – CSAR 1D IRF

CSAR L-Band

Stripmap L-Band


Tomography CSAR

Similar to Computer-aided Tomography 360°

Resolves altitude ambiguities

Shadow “removal”

a

b

Terrain

y x

z


Tomography CSAR– Simulated 3D IRF

yx

3D

2D Slice

Surface – 2D Slice

y x

z

Ishimaru, IEEE TGRS, 1998


Outline

Circular SAR (CSAR)



Experimental Setup and Results

Conclusions


Challenges of CSAR Processing

Topography accommodation

Real Track

Time efficient algorithm

High accuracy in amplitude and phase



Key points of FFBP (L. Ulander et al., IEEE TAES 2003):

Recursive division of the synthetic aperture (no cost)

After the division, the smallest sub-apertures are back-projected on a polar grid centred on each sub-aperture (~N3/2k)

Recursive addition of the sub-apertures by means of interpolations between polar grids (quality-dependent)



L/8 L/8 L/8 L/8 L/8 L/8

L/4 L/4

L/2

L/4 L/4

L/2

L/8 L/8

L

FOCUSED IMAGE

Lm BP

P2P

P2P

P2P

P2Final Grid

k2 Lmk=1

k=2

k=3

k2 Lm

k2 Lm

k2 Lm k2 Lm

k2 Lm

k2 Lm

Ulander et al, IEEE TAES, 2003


Why Polar Coordinates?

kr

krr

rx

kr

kx

Spatial Domain (small sub-aperture) Frequency Domain

Polar to Cartesian

2D FFT

2D FFT


x…

y x

z

FFBP for Spotlight/Stripmap – P2P


Outline

Circular SAR (CSAR)



Experimental Setup and Results

Conclusions


Modifications of FFBP for CSAR

The orientation of the polar grid for each sub-aperture changes following the circular trajectory.

The polar-to-polar interpolation needs to project first to ground coordinates and then back to the new polar centre.

The DEM must be generated (interpolated) for each polar centre.


FFBP for CSAR - Geometry

Top View

x

y



Top View

x

y


FFBP CSAR - P2P Interpolation

Zoom Top View

to

Ground range

Project

Translate

Rotate

Get and



Top View

.


Outline

Circular SAR (CSAR)




Conclusions


FFBP CSAR - Simulation

PRF 400Hz

Band L

BW 94MHz

Radius 4500m

Height 4000m

Terrain 700m

.


FFBP CSAR - Simulation

*Interpolator Knab Pulse of 21 points

BP vs FFBP

Knab, IEEE TIT, 1979


FFBP CSAR - Performance Speed Up

System, Geometry, Hardware, Interpolator

BP CPU ~238days

25000 x 25000 pixels

Speed up factor

BP GPU ~3 days

FFBP CPU ~11 hrs

FFBP GPU ~3 hrs


DLR’s (German Aerospace Center) E-SAR SystemLidar DEM availableKaufbeuren, Germany (2008)Fully Polarimetric: HH-HV-VV Carrier Frequency: 1.3GHz (L-Band)Bandwidth: 94MHzHeight Mean: ~3,200mCircle Radius: ~4,500mRoll Angle: ~10°Depression Angle: ~30°

Experimental Setup


Experimental Results - BP vs FFBP

Optical Image CSAR Image

150 x 150 m; Δφ=360°


Experimental Results - BP vs FFBP

1.0

0.99

10°

-10°

0°

Coherence Interferogram

Coh. Std. Dev. 0.000599 Phase Std. Dev. 1.7 °


Polarimetric Results - Subapertures

Pauli

1240 x 1240 m; Δφ=10°


CSAR vs Strimap SAR

1500 x 1500 mE-SAR L-band, 94MHz bandwidth


CSAR vs Strimap SAR

E-SAR L-band, 94MHz bandwidth



CSAR vs Strimap SAR



CSAR vs Strimap SAR

180 x 180 m



Circular SAR vs Strimap SAR

180 x 180 m


DEM + 0m

Tomography CSAR

DEM + 2m DEM + 3m DEM + 4m



Luneberg Lens

1500 x 1500 m


Tree


Tomography CSAR -5m < H < 15m

300 x 300 m


FFBP adapted to CSAR successfully:Topography accommodation Real trackHigh improvement in the Speed-up FactorHigh accuracy

Implementation in a graphic processor unit (GPU)

Experimental results with DLR’s E-SAR data have been used to validate the algorithm

Currently processing new “multi-circular” F-SAR campaign

Conclusions


Thanks for your attention!

Octavio Ponce: [email protected]

Pau Prats: [email protected]

DLR (German Aerospace Center)

HR (Microwaves and Radar Institute)


References

H. Oriot, H. Cantalloube, “Circular SAR imagery for urban remote sensing” ,EUSAR 2008.

A. Ishimaru, Chan, Kuga, “An Imaging Technique Using Confocal Circular Synthetic Aperture Radar”, IEEE Transactions on Geoscience and Remote Sensing, Vol. 36, No.5, Septemper 1998.

M. Soumekh, “Synthetic Aperture Radar Signal Processing with Matlab Algorithms”, John Wiley & Sons, Inc.

M. Pinheiro, P. Prats, R. Scheiber, M. Nannini, and A. Reigber, “Tomographic 3D reconstruction from airborne circular SAR,” in Geoscience and Remote Sensing Symposium, 2009 IEEE International, IGARSS 2009, 2009, vol. 3, pp. III–21 – III–24.

Lars M. H. Ulander and et. al., “Synthetic-Aperture Radar Processing Using Fast Factorized Back-Projection,” IEEE Transactions on Aerospace and Electronic Systems, vol. 39, no. 3, pp. 760–776, July 2003.

M. Rodriguez-Cassola, P. Prats, G. Krieger, and A. Moreira, “Efficient Time-Domain Focussing for General Bistatic SAR Configurations: Bistatic Fast Factorised Backprojection,” in European Conference on Synthetic Aperture Radar (EUSAR), Jun 2010.


FFBP for CSAR – Computational Load


Knab Pulse Band-Limited Interpolation

Knab, IEEE TIT, 1979


Hardware

CPU GPU

Processor Intel® Xeon® Tesla® C2070

RAM 24GB 6GB

Cores 8 488

Clock 2.4GHz 1.15GHz

CC 2.0


Acquisition Geometry

Integratedreflectivity

= reflectivityfunction

* transmitted radarsignal



IlluminationFlight Track

-60dB

0dB-6000

[m] 0

6000

-6000 0 6000 [m]


FFBP for CSAR – 2D Spectrum Polar

0.70° 1.40° 2.81° 5.62° 11.25°

22.5° 45° 90° 180°

kkr


FFBP for CSAR – Flow diagram

Cartesian DEM

Polar DEM

Translation

Rotation

Interpolate to regular (r,α)

Stop splitting

Split Data

Range Compressed Data Final cartesian grid

Compute polar grids (r,α,DEM)

Perform DBP

FFBP CSAR Recursive Kernel

FFBP CSARRecursive Kernel

P2P Interp

Compute polar grids (r,α,DEM)

Interpolate Subimage final grid

P2C Interp

Interpolate Subimages

A

A

Focused Image

No Yes

No No

YesYes

IGARSS11_FFBP_CSAR_v3.ppt

Technology

Transcript of IGARSS11_FFBP_CSAR_v3.ppt