2011 International Geoscience & Remote Sensing
Symposium
Geo-location error correction for
Synthetic Aperture Radar image
Using the ground control point
29. July, 2011
Soo H. Rho, Jung Kim and Young. K Kwag
Radar Signal Processing Lab.
Department of Avionics, Korea Aerospace University, Seoul, Korea
KOREA AEROSPACE UNIV. RSP
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IGARSS 2011 (24-29, July)
To be Presented
 Introduction
 Spaceborne SAR Geometry
 SAR Geo-location Error
 Multiple Target Distortion
 Overview Simulation
 Proposed Algorithm
 Simulation Results
 Conclusions
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IGARSS 2011 (24-29, July)
Introduction
 SAR Geometric Calibration
─ Geometric Correction
•
Processing step where the image is re-sampled from its natural distorted
projection into an actual image in a real coordinate system
 Geocoding for standard map projection such as UTM, WGS
Geolocation
─
•
Accurate target location decided by SAR sensor parameter and the Earth
model
─ Geometric Calibration
•
Process of measuring the various error sources such as sensor payload
platform ephemeris errors, relative target height error, and SAR signal
processing errors.
 Necessity
─ In the real operating environment, the SAR estimation errors always
exist
─ Accuracy of slant range measurement, Doppler centroid estimation
performance, SAR operation characteristics (Side-looking) are to be
analyzed and corrected in the process of the SAR image utilization.
KOREA AEROSPACE UNIV. RSP
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IGARSS 2011 (24-29, July)
Spaceborne SAR Geometry
•
Azimuth:
Direction aligned with the net sensor motion
•
Zero Doppler Plane:
Plane containing the sensor and is perpendicular to
the platform velocity vector
•
Range of closest approach R2:
Range when zero Doppler line crosses the target
•
Position of closest approach P2 :
Closest position of sensor to the target
•
Zero Doppler time:
Time of the closest approach
[Geometry of Side-looking SAR]
[SAR Image Formation Process]
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IGARSS 2011 (24-29, July)
Comparison of E/O & SAR Image
[EO Image]
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[SAR Image]
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IGARSS 2011 (24-29, July)
SAR Geo-location Error
Geo-location Error
Earth
Sensor
Platform
•Skewed Image
•PRF Fluctuation
•Image Orientation
•Range Non-Linearity
•Electronic Time Delay
•Yaw Angle
•Incidence Angle
•Pitch Angle
•Target Height
•Doppler Centroid
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IGARSS 2011 (24-29, July)
Geo-Location Error/Correction Method
 Error Source
SAR sensor
- Electronic Time Delay
- Slant Range Error
 Effect of Error
Effect of Error
- Range Location
- Incidence Angle Estimation
- Range Scale
- PRF Fluctuation
- Azimuth Scale
Earth
Earth
- Deskew
- Target Height
Platform
Platform
- Inclination Angle
- Image Orientation Error
- Yaw Angel Error
- Pitch Angle Error
- Squint Angle
- Doppler Centroid
- Side-looking
KOREA AEROSPACE UNIV. RSP Lab.
- Internal Calibration
- Geometric Calibration
- Azimuth Skew
- Range Non-Linearity
- Foreshortening, Layover,
Shadowing
- Earth Rotation
 Geo-location Error
Correction Method
- Ground Projection
- Image Rotation
- Terrain Correction
Ground Control Point
DEM, DSM
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Multiple Target Distortion
 Multiple Target Distortion
SAR
Rc
Re
Rg
c
e
b
g
d
Nadir
a
f
Shadow
Regions
Foreshortened
Regions
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Layover
Regions
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Overview of Simulation
 Selection of GCP
─ SAR images contain speckle noise. Thus, the GCPs that are used
in EO (Electro Optical) images is no longer effective.
─ As a result, distinctive physical features on the ground that are
readily identifiable from SAR image should be regarded as GCPs.
─ Examples: Runway, Intersection, Huge Building, cultivated land
 Procedure
─ The first step is the selection and extraction of GCP from SAR
and reference (EO) image. For the GCP extraction from satellite
radar image, easily seen objects such as intersections and
artificial structures with large RCS are chosen as reference points.
Since the GCP(Ground Control Point) which is often used in EO
images cannot be used for SAR Images due to speckle noise.
─ The second step is image transformation for GCP matching using
the each extracted points of SAR and EO image.
─ In the last step, RMSE values are calculated comparing the geolocation error corrected image and EO image.
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IGARSS 2011 (24-29, July)
Proposed Algorithm
SAR Image
: Input the Same Region Image
Extract GCP
Extract GCP, Check Point
: Extract the GCP, Check Point
Extract GCP
Coordinates
Extract GCP
Coordinates
Reference Image
Extract
Check Point
Image Transform
Extract Check
Point Coordinates
: Extract GCP Coordinates
: Image Transform (Projective Transform)
Extract Check Point
Coordinates
Comparison
: Image Matching, Calculation of RMSE
Geo-located
SAR Image
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Simulation Image
 RADARSAT-1
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16
24
15
23
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19
22
21
1
2
─ Seoul, Korea
18
20
─ Resolution : 10m x 10m
14
4
12
3
11
7
5
─ Error Corrected SAR
Image (Using SAR
General Information)
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6
8
9
10
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[Error Corrected SAR Image]
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Before Error Correction
 Before Using GCP
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25
25
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24
15
24
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23
15
19
23
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1
21
21
19
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18
20
1
2 2
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+ : EO Point (red)
14
4
4
12
33
13
12
11
7
5
+ : SAR Point
(yellow)
14
13
11
7
RMSE [m]
5
6 6
[Easting, Northing]
8
9
8
RMSE [Overall]
-1757.88
350.05
1792.39
9
10
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[Before Using GCP]
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After Error Correction (Using GCP)
 After Error correction Image (Using GCP)
─ EO point(red)/SAR point(yellow)
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24
15
17
23
19
22
18
20
21
1
2
14
4
12
3
13
11
5
7
RMSE [m]
6
[Easting, Northing]
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RMSE [Overall]
-5.68
2.35
6.14
9
10
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[After Error Correction]
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Comparison of RMSE
Northing : 454.05m
Easting : 1212.20m
Overall : 1294.45m
RMSE - SAR Image with Error
5000
RMSE [m]
4000
3000
Northing
2000
Easting
1000
Overall
0
1
-1000
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
GCP Number
Northing : 2.49m
Easting : 5.87m
Overall : 6.38m
RMSE - SAR Image without Error
100
RMSE [m]
80
60
Northing
40
Easting
20
Overall
0
-20
1
2
3
4
5
6
7
8
9
10
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14
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18
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GCP Number
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Simulation Results
[Reference Image]
[Using SAR General Information]
[Using GCP]
RMSE [m]
Region
Using SAR General Information
Using GCP
Northing
Easting
Overall
Northing
Easting
Overall
Mountain Area
855.43
-3807.3
3902.24
24.44
32.15
40.39
Urban Area
13.14
-391.59
391.81
1.37
-6.96
7.12
Total
454.05
1212.20
1294.45
2.49
5.87
6.38
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IGARSS 2011 (24-29, July)
Conclusions
 Geolocation error correction method is essential for SAR
image utilization
 New geo-location error correction method is proposed
using GCP.
 The performance of the proposed algorithm has been
evaluated in terms of the RMSE distance by correcting
foreshortening and layover and shadowing using the
SAR image.
 The proposed algorithm shows good performance in
correcting a geo-location error with aid of GCP data
compared to the case of the general SAR parameter
information without GCP. Performance of the proposed
method is improved especially in mountain area.
KOREA AEROSPACE UNIV. RSP Lab.
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IGARSS 2011 (24-29, July)
Thank you for your attention !
Contact author:
Prof. Young K. Kwag
ykwag@kau.ac.kr
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IGARSS 2011 (24-29, July)