Geodetically Accurate InSAR Data Processor for Time Series Analysis  Howard Zebker, Piyush Shanker, Cody Wortham, Scott He...
Modern applications need better geodetic accuracy <ul><li>InSAR and time series methods (PS, SBAS) require precise SLC ali...
Need for new processor <ul><li>Existing processing packages largely geodetically inaccurate </li></ul><ul><li>Pixels place...
Approach <ul><li>Use precise orbits to find exact (~10 cm error) satellite position </li></ul><ul><li>Choose a reference o...
Definitions for orbital geometry Reference orbit Orbit track projected on reference sphere Coordinate origin at center of ...
Remember the basics Phase and range  relations Doppler relations
Focus and position equations in our geometry
SCH coordinate system r c  – local radius of curvature, not Earth radius s – along track distance on local sphere from ref...
Geometry for motion compensation distance and phase Actual satellite position Satellite position on reference orbit at sam...
Finding the position on the reference orbit for an actual spacecraft location
Motion compensation distance calculation Motion compensation baseline is difference between actual range r’ and reference ...
Motion compensation algorithm Derivation of reference distance r: Mocomp distance and phase corrections:
Phase history for mocomped scatterer Compare phase histories for r act (t) and r(t)
Focus corrections Quadratic phase correction from processing at wrong distance: Frequency domain phase term from range-var...
Topographic correction <ul><li>Processor computes SLCs assuming perfectly spherical Earth </li></ul><ul><li>No easy closed...
Iterative topography correction Topographic phase correction:
Impulse response Impulse resolution: 5.3 m range, 4.0 m azimuth Figure for mocomp baseline of 1500 m (InSAR baseline 3km)
Single look complex image of SFO
Geodetic accuracy – Pinon Flat Corner Reflector Locations <ul><li>Latitude Longitude Latitude Longitude </li></ul><ul><li>...
Geodetic accuracy – Image offsets from SRTM DEM <ul><li>Range offset Azimuth offset Additional stretch </li></ul><ul><li>S...
Ventura, CA – Atmospheric phases
Hawaii – deformation plus atmosphere
Iceland – significant ionospheric artifact
Correlation images Ventura Hawaii Iceland
Computational efficiency <ul><li>Implemented on multicore desktop using F90 and Python scripting </li></ul><ul><li>Computa...
Summary <ul><li>InSAR and time series analysis requires precise image pixel locations </li></ul><ul><li>Imprecise location...
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TH1.L09 - GEODETICALLY ACCURATE INSAR DATA PROCESSOR FOR TIME SERIES ANALYSIS

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TH1.L09 - GEODETICALLY ACCURATE INSAR DATA PROCESSOR FOR TIME SERIES ANALYSIS

  1. 1. Geodetically Accurate InSAR Data Processor for Time Series Analysis Howard Zebker, Piyush Shanker, Cody Wortham, Scott Hensley Stanford University and Jet Propulsion Laboratory
  2. 2. Modern applications need better geodetic accuracy <ul><li>InSAR and time series methods (PS, SBAS) require precise SLC alignment from a variety of orbits </li></ul><ul><li>Merging SAR data with other types needs geolocated and orthorectified products </li></ul><ul><li>Processing many scenes (typically dozens) of one area needs to be efficient and on the desktop </li></ul>
  3. 3. Need for new processor <ul><li>Existing processing packages largely geodetically inaccurate </li></ul><ul><li>Pixels placed at wrong place </li></ul><ul><li>Lots of resampling to find offsets, and this is where many processors fail </li></ul><ul><li>Now have precise orbits </li></ul><ul><li>Multicore processors have untapped cycles we can use to speed up processing time </li></ul>
  4. 4. Approach <ul><li>Use precise orbits to find exact (~10 cm error) satellite position </li></ul><ul><li>Choose a reference orbit for multiple scenes so images are nearly aligned – small offsets </li></ul><ul><li>Reference orbit not physically realizable without constant acceleration, so it’s “virtual” </li></ul><ul><li>Use motion compensation method to make spacecraft “fly” on chosen trajectory </li></ul><ul><li>Be careful to keep geometrical info throughout </li></ul>
  5. 5. Definitions for orbital geometry Reference orbit Orbit track projected on reference sphere Coordinate origin at center of sphere with local Earth radius of curvature Point to be imaged Instantaneous squint angle
  6. 6. Remember the basics Phase and range relations Doppler relations
  7. 7. Focus and position equations in our geometry
  8. 8. SCH coordinate system r c – local radius of curvature, not Earth radius s – along track distance on local sphere from reference point c – across-track distance on local sphere h – height above local sphere
  9. 9. Geometry for motion compensation distance and phase Actual satellite position Satellite position on reference orbit at same squint direction (Figure is projection of imaging geometry onto the reference sphere)
  10. 10. Finding the position on the reference orbit for an actual spacecraft location
  11. 11. Motion compensation distance calculation Motion compensation baseline is difference between actual range r’ and reference orbit range r
  12. 12. Motion compensation algorithm Derivation of reference distance r: Mocomp distance and phase corrections:
  13. 13. Phase history for mocomped scatterer Compare phase histories for r act (t) and r(t)
  14. 14. Focus corrections Quadratic phase correction from processing at wrong distance: Frequency domain phase term from range-varying motion compensation phase:
  15. 15. Topographic correction <ul><li>Processor computes SLCs assuming perfectly spherical Earth </li></ul><ul><li>No easy closed form solution for position so use iterative method to find pixel location in 3-space </li></ul><ul><li>Apply phase correction based on pixel elevation </li></ul>
  16. 16. Iterative topography correction Topographic phase correction:
  17. 17. Impulse response Impulse resolution: 5.3 m range, 4.0 m azimuth Figure for mocomp baseline of 1500 m (InSAR baseline 3km)
  18. 18. Single look complex image of SFO
  19. 19. Geodetic accuracy – Pinon Flat Corner Reflector Locations <ul><li>Latitude Longitude Latitude Longitude </li></ul><ul><li>Measurement (deg) (deg) error (m) error (m) </li></ul><ul><li>  </li></ul><ul><li>Reflector aligned with ascending orbit </li></ul><ul><li>  </li></ul><ul><li>InSAR location, 33.61233 -116.4570 9 -18 </li></ul><ul><li>unregistered image </li></ul><ul><li>InSAR location, 33.61215 -116.4567 -11 9 </li></ul><ul><li>registered image </li></ul><ul><li>  </li></ul><ul><li>Ground GPS 33.61225 -116.4568 -- -- </li></ul><ul><li>survey </li></ul><ul><li>  </li></ul><ul><li>Reflectors aligned with descending orbit </li></ul><ul><li>  </li></ul><ul><li>InSAR location, 33.61215 -116.4579 -11 0 </li></ul><ul><li>unregistered image </li></ul><ul><li>InSAR location, 33.61213 -116.4577 -13 18 </li></ul><ul><li>registered image </li></ul><ul><li>Ground GPS 33.61225 -116.4579 -- -- </li></ul><ul><li>Survey </li></ul><ul><li>InSAR location, 33.60729 -116.4517 -9 9 </li></ul><ul><li>unregistered image </li></ul><ul><li>InSAR location, 33.60727 -116.4516 -11 18 </li></ul><ul><li>registered image </li></ul><ul><li>Ground GPS 33.60737 -116.4518 -- -- </li></ul><ul><li>survey </li></ul>
  20. 20. Geodetic accuracy – Image offsets from SRTM DEM <ul><li>Range offset Azimuth offset Additional stretch </li></ul><ul><li>Scene at center (m) at center (m) Range (m) Azimuth (m) </li></ul><ul><li>  </li></ul><ul><li>Ventura -15.8 18.2 9.4 15.2 </li></ul><ul><li>  </li></ul><ul><li>Hawaii -21.5 24.0 14.1 25.4 </li></ul><ul><li>  </li></ul><ul><li>Iceland 2.0 2.9 44.0 29.4 </li></ul>
  21. 21. Ventura, CA – Atmospheric phases
  22. 22. Hawaii – deformation plus atmosphere
  23. 23. Iceland – significant ionospheric artifact
  24. 24. Correlation images Ventura Hawaii Iceland
  25. 25. Computational efficiency <ul><li>Implemented on multicore desktop using F90 and Python scripting </li></ul><ul><li>Computational modules parallelized with OpenMP </li></ul><ul><li>Typical ALOS interferogram ~2-4 minutes </li></ul><ul><li>Working with JPL to produce a package to be distributed to community </li></ul><ul><li>At present we use a standalone version compiled under *nix </li></ul>
  26. 26. Summary <ul><li>InSAR and time series analysis requires precise image pixel locations </li></ul><ul><li>Imprecise locations make processing slow and unreliable </li></ul><ul><li>With precise orbits, motion compensation, and particular geometry processor equations are fairly simple and efficient to compute </li></ul><ul><li>Accuracies of 10 m easy to achieve, probably 1 m with further development </li></ul>

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