Iterative calibration of relative platform position a new_method for_baseline_estimation
Transcript of Iterative calibration of relative platform position a new_method for_baseline_estimation
![Page 1: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/1.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion
Iterative Calibration of Relative PlatformPosition:
A New Method for Baseline Estimation
Tiangang Yin1, Emmanuel Christophe1, Soo Chin Liew1 ,Sim Heng Ong2
1CENTRE FOR REMOTE IMAGING, SENSING AND PROCESSING
2DEPT. OF ELECTRICAL AND COMPUTER ENGINEERING,NATIONAL UNIVERSITY OF SINGAPORE
![Page 2: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/2.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion
Outline
1 Motivation
2 IntroductionConceptBaseline CalibrationExpand
3 AlgorithmCoordinate SystemIteration
4 Validation
5 Conclusion
![Page 3: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/3.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion
Motivation
We have already knowBaseline precision is significant to the interferometricaccuracyPrecise estimation is required
IdeaInterferometric result can provide information on baselineConcept can be extended under multiple passes condition,from baseline to individual sensor positionIteration and Constraint
![Page 4: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/4.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion Concept Baseline Calibration Expand
Outline
1 Motivation
2 IntroductionConceptBaseline CalibrationExpand
3 AlgorithmCoordinate SystemIteration
4 Validation
5 Conclusion
![Page 5: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/5.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion Concept Baseline Calibration Expand
Concept
Baseline ConceptRefer to the relative distance between two sensorsHighlight “relative”
depends on the chosen master image as coordinate originbuild a coordinate system base on master image position,normally described using “parallel” and “perpendicular”
Initially estimated using orbital information, interpolatedfrom platform position vector
![Page 6: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/6.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion Concept Baseline Calibration Expand
Baseline ErrorThe root of baseline estimation error is the inaccurateplatform position from orbit dataIt can happen on any of the interferometric pairAll the interferograms will be wrong with the sameinaccurate path
![Page 7: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/7.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion Concept Baseline Calibration Expand
Geometrical ConstraintThe geometric representation of multiple platform positionscan be constructed as polygon(2D) or polyhedron(3D)Using the orbit estimated baseline, this geometricrepresentation can be constructed
![Page 8: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/8.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion Concept Baseline Calibration Expand
Baseline CalibrationIn the past method, error of perpendicular baseline can bereduced by using GCP or reference DEMHowever, the correction is only on the relative distance. Noguarantee for the corrected baseline.
![Page 9: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/9.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion Concept Baseline Calibration Expand
Expand
From baseline to relative positionWhen more information on platform position can be interpretedfrom data, global constraint of platform position is needed.Without constraint, the geometry of platform positions willbreak.
![Page 10: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/10.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion Concept Baseline Calibration Expand
Expand
Because the problem will become very complicated in 3Dwhen more passes are used
An iterative optimization method will be provided undergeometry constraintGlobal baseline calibrationDetection and quantitative calibration of any pass withinaccurate orbit information
![Page 11: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/11.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion Coordinate System Iteration
Outline
1 Motivation
2 IntroductionConceptBaseline CalibrationExpand
3 AlgorithmCoordinate SystemIteration
4 Validation
5 Conclusion
![Page 12: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/12.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion Coordinate System Iteration
Coordinate System
Requirementeasy to transfer system from one master image to anothererror is small enough
TCN (Track, Cross-track and Normal) coordinates is chosen
n =−~P| P |
c =n × ~V
| n × ~V |t = c × n (1)
![Page 13: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/13.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion Coordinate System Iteration
Transfer Equation: ~Bji ' −~BijIs it valid?
Assumption can be made that all of the platform have thesame direction of ~VImage pixels within one range row will share the samebaseline TCN coordinates
∆θ = arctan
√| ~Bij · c |2 + | ~Bij · t |2
Ai + R(2)
Ai : the platform altitude of image i (691.65 km for ALOS)R: the radius of the earth (6378.1 km)
![Page 14: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/14.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion Coordinate System Iteration
System Error
The baseline component along t is very smallTherefore, for baseline of 1 km along c, the axis error is0.0081◦
the baseline error is ~Bij · c × tan ∆θ ' 14 cm for this systemConclude: TCN coordinates system will be considered atcorresponding point between all passes
~Bji ' −~Bij (3)
![Page 15: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/15.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion Coordinate System Iteration
Iteration: Starting PointK + 1 passes over same areaDifferential interferogram and baseline is generated for allcombinationsProcessed with both baseline vector and baselinechanging rateInitialization:
~Bji = −~Bij~Bji = −~Bij (4)
![Page 16: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/16.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion Coordinate System Iteration
Iteration Steps
Take one pass as master image, calculate the baselineerror to be corrected
Average the result: ∆~P(n)i = 1
K ×∑
j 6=i ∆~Bij
Update all the baseline vectors: ~Bij = ~Bij + ∆~P(n)i
A weight coefficient 1n can be added before ∆~P(n)
i to slow down the convergence
Update the reversed baseline ~Bji
Change another master image and go back to first step,until all of the images have been taken once as masterimageCalculate the total displacement of all platform:∆~P(n) =
∑K +1i=1 | ∆~P(n)
i |Iteration n finished, Take n = n + 1 and restart
![Page 17: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/17.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion Coordinate System Iteration
Iteration Steps
Take one pass as master image, calculate the baselineerror to be correctedAverage the result: ∆~P(n)
i = 1K ×
∑j 6=i ∆~Bij
Update all the baseline vectors: ~Bij = ~Bij + ∆~P(n)i
A weight coefficient 1n can be added before ∆~P(n)
i to slow down the convergence
Update the reversed baseline ~Bji
Change another master image and go back to first step,until all of the images have been taken once as masterimageCalculate the total displacement of all platform:∆~P(n) =
∑K +1i=1 | ∆~P(n)
i |Iteration n finished, Take n = n + 1 and restart
![Page 18: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/18.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion Coordinate System Iteration
Iteration Steps
Take one pass as master image, calculate the baselineerror to be correctedAverage the result: ∆~P(n)
i = 1K ×
∑j 6=i ∆~Bij
Update all the baseline vectors: ~Bij = ~Bij + ∆~P(n)i
A weight coefficient 1n can be added before ∆~P(n)
i to slow down the convergence
Update the reversed baseline ~Bji
Change another master image and go back to first step,until all of the images have been taken once as masterimageCalculate the total displacement of all platform:∆~P(n) =
∑K +1i=1 | ∆~P(n)
i |Iteration n finished, Take n = n + 1 and restart
![Page 19: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/19.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion Coordinate System Iteration
Iteration Steps
Take one pass as master image, calculate the baselineerror to be correctedAverage the result: ∆~P(n)
i = 1K ×
∑j 6=i ∆~Bij
Update all the baseline vectors: ~Bij = ~Bij + ∆~P(n)i
A weight coefficient 1n can be added before ∆~P(n)
i to slow down the convergence
Update the reversed baseline ~Bji
Change another master image and go back to first step,until all of the images have been taken once as masterimageCalculate the total displacement of all platform:∆~P(n) =
∑K +1i=1 | ∆~P(n)
i |Iteration n finished, Take n = n + 1 and restart
![Page 20: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/20.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion Coordinate System Iteration
Iteration Steps
Take one pass as master image, calculate the baselineerror to be correctedAverage the result: ∆~P(n)
i = 1K ×
∑j 6=i ∆~Bij
Update all the baseline vectors: ~Bij = ~Bij + ∆~P(n)i
A weight coefficient 1n can be added before ∆~P(n)
i to slow down the convergence
Update the reversed baseline ~Bji
Change another master image and go back to first step,until all of the images have been taken once as masterimage
Calculate the total displacement of all platform:∆~P(n) =
∑K +1i=1 | ∆~P(n)
i |Iteration n finished, Take n = n + 1 and restart
![Page 21: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/21.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion Coordinate System Iteration
Iteration Steps
Take one pass as master image, calculate the baselineerror to be correctedAverage the result: ∆~P(n)
i = 1K ×
∑j 6=i ∆~Bij
Update all the baseline vectors: ~Bij = ~Bij + ∆~P(n)i
A weight coefficient 1n can be added before ∆~P(n)
i to slow down the convergence
Update the reversed baseline ~Bji
Change another master image and go back to first step,until all of the images have been taken once as masterimageCalculate the total displacement of all platform:∆~P(n) =
∑K +1i=1 | ∆~P(n)
i |
Iteration n finished, Take n = n + 1 and restart
![Page 22: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/22.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion Coordinate System Iteration
Iteration Steps
Take one pass as master image, calculate the baselineerror to be correctedAverage the result: ∆~P(n)
i = 1K ×
∑j 6=i ∆~Bij
Update all the baseline vectors: ~Bij = ~Bij + ∆~P(n)i
A weight coefficient 1n can be added before ∆~P(n)
i to slow down the convergence
Update the reversed baseline ~Bji
Change another master image and go back to first step,until all of the images have been taken once as masterimageCalculate the total displacement of all platform:∆~P(n) =
∑K +1i=1 | ∆~P(n)
i |Iteration n finished, Take n = n + 1 and restart
![Page 23: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/23.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion
Outline
1 Motivation
2 IntroductionConceptBaseline CalibrationExpand
3 AlgorithmCoordinate SystemIteration
4 Validation
5 Conclusion
![Page 24: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/24.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion
Data Over Singapore8 passes of PALSAR over the Singapore betweenDecember 2006 and September 2009 are usedSRTM is used as reference DEMGAMMA software is used for the interferogramsPython used for programming
Starting Point:
![Page 25: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/25.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion
Results:Relative Position Iteration
−200 −100 0 100 200 300−150
−100
−50
0
50
100
150
200
250
Relative Cross−Track Coordinate(m)
Rel
ativ
e N
orm
al C
orrd
inat
e(m
)
20081226
20061221
20070923
20090928
20090210
20070623
20081110
20090628
Before iterationAfter iteration
Click t
o buy N
OW!PD
F-XChange Viewer
ww
w.docu-track.com Clic
k to b
uy NOW
!PD
F-XChange Viewer
ww
w.docu-track.c
om
(a) Global Relative Position Iteration
−95 −94.5 −94 −93.5 −93
159
159.5
160
Relative Cross−Track Coordinate(m)
Rel
ativ
e N
orm
al C
orrd
inat
e(m
)
Before iterationAfter iteration
(b) for 20070923
72 74 76 78
11
12
13
14
15
16
Relative Cross−Track Coordinate(m)
Rel
ativ
e N
orm
al C
orrd
inat
e(m
)
Before iterationAfter iteration
(c) for 20090928
![Page 26: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/26.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion
Results:Displacement plotting without weightcoefficient
The totaldisplacement∆~P(n)
converges
0 1 2 3 4 5 6 7 8 9 100
2
4
6
8
10
12
14
16
18
20
Interation Number n
Dis
plac
emen
t ∆P
(m)
Total Displacement ∆P(n)
2008122620061221200709232009092820090210200706232008111020090628
![Page 27: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/27.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion
Results:Displacement plotting with weight coefficient
Theconvergenceis slower butresult in asmaller valueSpeed canneither be tooslow nor toofast
0 1 2 3 4 5 6 7 8 9 100
2
4
6
8
10
12
14
16
18
20
Interation Number n
Dis
plac
emen
t ∆P
(m)
Total Displacement ∆P(n)
2008122620061221200709232009092820090210200706232008111020090628
![Page 28: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/28.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion
Results:Differential interferogram after calibration
71 72 73 74 75 76 77 78 79
11
12
13
14
15
16
Relative Cross−Track Coordinate(m)
Rel
ativ
e N
orm
al C
orrd
inat
e(m
)
Before iterationAfter iteration
![Page 29: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/29.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion
Outline
1 Motivation
2 IntroductionConceptBaseline CalibrationExpand
3 AlgorithmCoordinate SystemIteration
4 Validation
5 Conclusion
![Page 30: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/30.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion
Conclusion
ConceptSatellite platform position can be relatively calibrated frommultiple interferograms
ResultThe SAR passes which gives inaccurate platform positionare successfully detected and calibrated
DisadvantagePlatform position can only be calibrated alongperpendicular baseline
![Page 31: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/31.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion
Conclusion
ConceptSatellite platform position can be relatively calibrated frommultiple interferograms
ResultThe SAR passes which gives inaccurate platform positionare successfully detected and calibrated
DisadvantagePlatform position can only be calibrated alongperpendicular baseline
![Page 32: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/32.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion
Conclusion
ConceptSatellite platform position can be relatively calibrated frommultiple interferograms
ResultThe SAR passes which gives inaccurate platform positionare successfully detected and calibrated
DisadvantagePlatform position can only be calibrated alongperpendicular baseline
![Page 33: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/33.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion
Conclusion
ConceptSatellite platform position can be relatively calibrated frommultiple interferograms
ResultThe SAR passes which gives inaccurate platform positionare successfully detected and calibrated
DisadvantagePlatform position can only be calibrated alongperpendicular baseline
![Page 34: Iterative calibration of relative platform position a new_method for_baseline_estimation](https://reader034.fdocuments.in/reader034/viewer/2022052507/558de5ae1a28abe2428b4710/html5/thumbnails/34.jpg)
IGARSS 2010, Honolulu
Motivation Introduction Algorithm Validation Conclusion
Conclusion
Possible ApplicationOrbit refinement for SARBaseline problem for deformation monitoring, likeearthquake