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IGARSSAirSWOTv2.ppt

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IGARSSAirSWOTv2.ppt

  1. 1. <ul><li>AirSwot: </li></ul><ul><li>A Calibration/Validation Platform For The SWOT Mission </li></ul><ul><li>Delwyn Moller, Ernesto Rodriguez, </li></ul><ul><li>James Carswell, Daniel Esteban-Fernandez </li></ul>
  2. 2. <ul><li>Ka-band SWOT Phenomenology Airborne Radar ( KaSPAR): AirSWOT’s radar payload </li></ul><ul><ul><li>Instrument configuration </li></ul></ul><ul><ul><li>Performance </li></ul></ul><ul><ul><li>Processing and products </li></ul></ul><ul><ul><li>Hardware heritage and development status </li></ul></ul><ul><li>AirSWOT calibration/validation Platform </li></ul><ul><ul><li>Auxiliary sensors </li></ul></ul><ul><ul><li>Platform </li></ul></ul><ul><ul><li>Timeline </li></ul></ul>Outline
  3. 3. Ka-band SWOT Phenomenology Airborne Radar (KaSPAR) <ul><li>Calibration/Validation Sensor </li></ul><ul><li>The high-precision swath elevation mapping capability will enable calibration and validation of SWOT with 3D measurements not currently achievable </li></ul><ul><li>Primary measurement product: </li></ul><ul><li>High accuracy elevation maps with ~5km swath (at 35kft) over ocean </li></ul><ul><ul><li>Traditional altimeter height retrieval to provide tie points for swath edges </li></ul></ul><ul><ul><li>Dedicated Science Campaigns: TBD </li></ul></ul><ul><li>Phenomenology </li></ul><ul><li>Multiple (elevation & temporal) baselines replicate and fully characterize SWOT sampling and geometry </li></ul><ul><li>Gather pre-mission data for SWOT over specific and varied science targets for: </li></ul><ul><ul><li>Classification (land/water and further) </li></ul></ul><ul><ul><li>Predicting performance and interpretability to extend the science impact beyond the mission requirements </li></ul></ul><ul><ul><li>Penetration into snow for cryospheric applications </li></ul></ul><ul><li>Provide high resolution spatial measurements of: </li></ul><ul><ul><li>Water temporal correlation </li></ul></ul><ul><ul><li>Elevation (both land and water) </li></ul></ul><ul><ul><li>Surface backscatter </li></ul></ul><ul><ul><li>Vegetation attenuation </li></ul></ul>
  4. 4. Swath Performance <ul><li>Two sets of transmit antennas: </li></ul><ul><ul><li>Illuminate inner (SWOT geometry) & outer swath to provide wide-swath coverage </li></ul></ul><ul><ul><li>Overlapping beams for inter-calibration </li></ul></ul>Random error across swath Parameter Value Unit Center Frequency 35.75 GHz Peak Transmit Power 40 W Platform Height 35 kft Swath Coverage “inner” “ outer” 1.4 5.0 km Bandwidth “inner” “ outer” 200 (min) 80 (min) MHz Mean height error “inner” “ outer” 1.2 * 2.3 ** cm Incidence angles “inner” “ outer” 1-5 4-27 deg
  5. 5. Measurements and Processing <ul><li>KaSPAR will make the following measurements*: </li></ul><ul><ul><li>Surface elevation maps of the water and land (land accuracy will be lessened) </li></ul></ul><ul><ul><ul><li>Swath of up to 5km depending on water state </li></ul></ul></ul><ul><ul><ul><li>Resolution variable but innate instrument 1-look resolution is 10 ’s of cm along-track and 10-5m range </li></ul></ul></ul><ul><ul><ul><li>Precision for ~50x50m posting is sub-3cm mean and assumes an ocean surface with 6m/s or greater winds </li></ul></ul></ul><ul><ul><li>Corresponding backscattered power and correlation maps </li></ul></ul><ul><ul><li>For outer incidence angles - surface radial velocity </li></ul></ul><ul><ul><li>Surface temporal correlation estimates </li></ul></ul>*all simultaneous including both “SWOT-like” and “mapping” swaths
  6. 6. Technology Support for SWOT: Calibration Loop <ul><li>To meet the phase calibration goals outlined above KaSPAR will implement calibration loops to verify a new technique SWOT plans to employ for channel phase calibration. </li></ul><ul><ul><li>This is to enable loopback phase calibration to greater accuracy than required strictly for KaSPAR(0.2 o budgeted) </li></ul></ul><ul><ul><li>Rather this will demonstrate calibration knowledge to millidegrees </li></ul></ul><ul><ul><ul><li>Matched filter tracks phase-changes in real-time by recording transmitted pulse through full transceiver path </li></ul></ul></ul><ul><ul><ul><li>SNR and stringent signal to leakage ratio requirements </li></ul></ul></ul><ul><ul><li>Success impact in terms of SWOT: </li></ul></ul><ul><ul><li>verify proposed SWOT calibration loop which enables relaxation of phase stability requirements since the method corrects for drift </li></ul></ul>
  7. 7. AirSWOT Technology Heritage and Infusion Multichannel, high-throughput digital system compatible with unpressurized unattended operation <ul><li>First demonstration of mm-wave SAR interferometry </li></ul><ul><ul><li>technology development & technique demonstration </li></ul></ul><ul><ul><li>Processor development is direct heritage for KaSPAR/AirSWOT </li></ul></ul>GLISTIN slotted waveguide DBF array produced IPY/AITT antenna design. HiWRAP: IIP & NASA SBIR GLISTIN-A: IPY & AITT AirSWOT SWOT cal/val sensor: ESTO & NASA SBIR Compact integrated assembly compatible across platforms (e.g. NASA King Air, Ikhana, Global Hawk, DC8). GLISTIN: IIP
  8. 8. KaSPAR Development Status <ul><li>Currently funded under a Phase II and Phase III NASA SBIR’s and NASA ESTO </li></ul><ul><li>Phase II started April 2010 with radar design and RF development for key assemblies </li></ul><ul><li>Complementary activities for digital development </li></ul><ul><li>Recent ESTO funding for system-level and processor development </li></ul>
  9. 9. Antenna Summary Narrow Beam Wide Beam Size 21.2 cm x 4.0 cm 21.2 cm x 14.5 cm Realized Gain 35.5 dBi 28.7 dBi HPBW: Ecut 4.0 deg 17.2 deg Hcut 3.2 deg 2.6 deg SLL: Ecut < -23 dB < -22 dB Hcut < -23 dB < -23 dBI Low CTE panel <ul><li>Radome not shown integrated with antennas </li></ul><ul><li>Patterns verified, measured on near-field range </li></ul>
  10. 10. Downconverters (4 of 7) Upconverter Transmitter IF RF Subassemblies <ul><li>Subassembly development complete and CW tested </li></ul><ul><li>Further characterization – eg temperature sensitivity underway </li></ul>x2 Upconverter
  11. 11. LO distribution Internal Calibration <ul><li>Subassembly development complete and CW tested </li></ul>RF Subassemblies (cont)
  12. 12. Solid-State Power Amplifier <ul><li>SSPA under development </li></ul><ul><li>Based on existing unit but accommodating new higher power MMIC’s with same combiner. </li></ul><ul><li>Timeline – November 2011 </li></ul><ul><li>Thermal assessment underway (complementary with GLISTIN-A activities) </li></ul>
  13. 13. Digital Receiver System Radar Controller / Waveform Generator 3.6 GSa/s – 12-bit ADC Board <ul><li>Conduction Cooled 3U solution. </li></ul><ul><li>Deployed on Global Hawk and ER-2 (HIWRAP system). </li></ul><ul><li>Support 4 FPGA Processing Modules (FPM) per system. </li></ul><ul><li>Each FPM can support up to 400 MHz bandwidth (100% duty). </li></ul><ul><li>Four Gigabit interfaces support > 400 MB/s sustained data recording rates. </li></ul><ul><li>ADC module is embedded in transceiver providing 3.6 GSa/s 12-bit sampling. </li></ul><ul><li>5 Gbps fiber communication between ADC module and FPM. </li></ul><ul><li>DDS/CTU supports synching of up to 8 ADC modules . </li></ul><ul><li>DDS/CTU supports arbitrary amplitude tapering, LFM, NLFM, fixed frequency and CW waveforms. </li></ul><ul><li>Fabrication will be completed in August/September 2011. </li></ul>
  14. 14. AirSWOT: Payload Sensors <ul><li>Two NASA airborne science facility sensors will be integrated with KaSPAR for the AirSWOT assembly: </li></ul><ul><ul><li>State-of-the-art Applanix 510 IMU (possibly 610) </li></ul></ul><ul><ul><li>DCS Near IR camera in aft port (cover field of view of radar with meter-level pixel size at 35kft). </li></ul></ul><ul><ul><ul><ul><li>Map inundation extent using both KaSPAR and the DCS </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Spatial resolutions of 50 cm – 1 m. </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Frames synchronized with the IMU and radar. </li></ul></ul></ul></ul><ul><ul><ul><ul><li>It will include a near-infrared band, ideal for mapping </li></ul></ul></ul></ul><ul><ul><ul><ul><li>inundation </li></ul></ul></ul></ul>Map of water-land interface pixels for the Tanana River, Alaska At each red pixel, there is potential for classification error in KaSPAR data.
  15. 15. AirSWOT: Platform considerations P3 Gulfstream King Air GlobalHawk /C130
  16. 16. Initial Platform: NASA King Air B200 <ul><li>Two available (DFRC and LARC) with nadir ports ready modified </li></ul><ul><li>Altitude 35kft </li></ul>
  17. 17. Near-term plans <ul><li>System-level I&T starting Winter 2011 </li></ul><ul><li>First engineering flights targeted for Spring 2012 </li></ul><ul><li>We need to formulate deployment plan for deployments pre-mission through SWOT calibration and validation (ie starting after engineering checkout ~ Fall 2012) </li></ul><ul><ul><li>Draft will be compiled for SWG meeting in October </li></ul></ul>
  18. 18. Backups
  19. 19. Example of Backscatter Dependence on Wind
  20. 20. Aircraft considerations: NASA Global Hawk <ul><li>Best for mimicking SWOT geometry </li></ul><ul><li>KaSPAR design is compatible with UAV deployment in the long-term </li></ul><ul><li>Altitude 65kft </li></ul><ul><li>Long duration </li></ul><ul><li>Payload area 120 ”long x 56” wide </li></ul><ul><li>ER2 also a possibility </li></ul>Payload area
  21. 21. The backscattered power as a function of incidence angle was used to solve for the normalized radar cross-section using the radar range equation: We know the antenna pattern and we assumed the following geometric optics approximation for  0 : Where s 2 is the mean-square slope and  hs is the small scale roughness. Estimation of  0 near-nadir
  22. 22. Airborne Velocity Mapping <ul><li>Ideal for targeted response (search and rescue, flood regions, pollutant spills, tidal flow patterns) </li></ul><ul><ul><li>two antennae separated by an along-track baseline B </li></ul></ul><ul><ul><li>one antenna transmits and one or both receive </li></ul></ul><ul><ul><li>images from each receive channel are interpolated to the same spatial locations </li></ul></ul><ul><ul><li>resultant images (separated in time by  = B/v , where v is the platform velocity) are interfered </li></ul></ul><ul><ul><li>the interferometric phase  is related to the radial scene velocity u as </li></ul></ul>Right: C-band radial velocity image over San Francisco bay. Pixel resolution ~10m and velocity precision ~10cm. Swath ~8-10km u B swath
  23. 23. Example Products/Data
  24. 24. KaSPAR Along-track Capability <ul><li>50 x 80 m posting - no ping-pong and 6m/s wind </li></ul><ul><li>Good for assimilation and discharge estimation modeling </li></ul><ul><li>Also for eddy dynamics, sea-ice etc </li></ul>
  25. 25. Processing and Products <ul><li>The products available from KaSPAR will be the following: </li></ul><ul><ul><li>Surface elevation maps of the water and land (land accuracy will be lessened) </li></ul></ul><ul><ul><ul><li>Swath of up to 5km depending on water state </li></ul></ul></ul><ul><ul><ul><li>Resolution variable but innate instrument 1-look resolution is 10 ’s of cm along-track and 10-5m range </li></ul></ul></ul><ul><ul><ul><li>Precision for ~50x50m posting is sub-3cm mean but assumes an ocean surface with 6m/s or greater winds </li></ul></ul></ul><ul><ul><li>Surface temporal correlation </li></ul></ul><ul><ul><li>For outer incidence angles - surface radial velocity </li></ul></ul><ul><ul><li>Corresponding backscattered power and correlation maps </li></ul></ul><ul><li>InSAR processing will build on the GLISTIN interferometric processor and calibration. Instrument and data calibration will provide greater challenges to achieve the accuracies wanted. The IMU and corrections for aircraft attitude is critical. </li></ul><ul><li>A facility near-IR camera will provide coregistered shoreline demarcation for classification verification </li></ul>
  26. 26. Variability of  0 (  i )
  27. 27. Swath Mapping Performance * Error Sources modeled Quantity Unit random SNR Derived from system radar-range equation for ocean at 6m/s wind Unitless ratio Geometric Derived for each baseline ISLR/MNR -13 dB Zero-range ambiguity Relative gain of 2-way antenna pattern from opposite side Unitless ratio systematic Receiver phase drift knowledge error 0.2 degrees Baseline deviation 20 microns Range timing accuracy 3 ns Mean height error performance (35kft, ocean) Inner subswath 1.8 cm Outer swath 2.3* cm
  28. 28. Predicted Height Accuracy for “SWOT” Subswath
  29. 29. Predicted Height Accuracy Across Swath
  30. 30. Processing and Products <ul><li>The products available from KaSPAR will be the following: </li></ul><ul><ul><li>Surface elevation maps of the water and land (land accuracy will be lessened) </li></ul></ul><ul><ul><ul><li>Swath of up to 5km depending on water state </li></ul></ul></ul><ul><ul><ul><li>Resolution variable but innate instrument 1-look resolution is 10 ’s of cm along-track and 10-5m range </li></ul></ul></ul><ul><ul><ul><li>Precision for ~50x50m posting is sub-3cm mean but assumes an ocean surface with 6m/s or greater winds </li></ul></ul></ul><ul><ul><li>Surface temporal correlation </li></ul></ul><ul><ul><li>For outer incidence angles - surface radial velocity </li></ul></ul><ul><ul><li>Corresponding backscattered power and correlation maps </li></ul></ul><ul><li>InSAR processing will build on the GLISTIN interferometric processor and calibration. Instrument and data calibration will provide greater challenges to achieve the accuracies wanted. The IMU and corrections for aircraft attitude is critical. </li></ul><ul><li>A facility near-IR camera will provide coregistered shoreline demarcation for classification verification </li></ul>
  31. 31. Strategies for Validation of KaSPAR Hydrologic Measurements <ul><li>Water Level and Slope: </li></ul><ul><li>Install pressure transducer water level loggers in rivers and lakes, recording water level changes every 15 minutes with mm-level precision. </li></ul><ul><li>Use differential GPS to obtain absolute elevations for each sensor. </li></ul><ul><li>Compare temporal and spatial variations in water surface elevation between KaSPAR and field data. </li></ul>Solinst Pressure Transducer Water Level Logger Setup for a pressure transducer sensor installed in a lake Examples of pressure transducer data for two river channels, Peace-Athabasca Delta, Canada Differential GPS Equipment used for surveying water levels in rivers and lakes. Sensor Viewgraph credit: Tamlin Pavelsky UNC-Chapel Hill
  32. 32. Strategies for Validation of KaSPAR Hydrologic Measurements <ul><li>River Discharge and Flow Velocity: </li></ul><ul><li>With help from the U.S. Geological Survey, obtain Acoustic Doppler Current Profiler (ADCP) measurements of river discharge coincident with AirSWOT data collection. </li></ul><ul><li>Use discharge measurements from existing river gauging stations to validate AirSWOT discharge algorithms. </li></ul>Photo courtesy USGS An Example of ADCP Data Viewgraph credit: Tamlin Pavelsky UNC-Chapel Hill
  33. 33. AirSWOT support for SWOT pre-mission <ul><li>Multiple (elevation & temporal) baselines replicate and fully characterize SWOT sampling and geometry </li></ul><ul><li>Gather pre-mission data for SWOT over specific and varied science targets for: </li></ul><ul><ul><li>Classification (eg: land/water, wet-land/water, ice/water etc) </li></ul></ul><ul><ul><li>Discharge algorithm validation </li></ul></ul><ul><ul><li>Water temporal correlation </li></ul></ul><ul><ul><li>Elevation (both land and water) </li></ul></ul><ul><ul><li>Surface backscatter </li></ul></ul><ul><ul><li>Vegetation attenuation </li></ul></ul><ul><ul><li>Elevation retrieval over vegetated water </li></ul></ul><ul><ul><li>Sea ice height measurement </li></ul></ul><ul><ul><li>Penetration into snow for cryospheric applications </li></ul></ul><ul><ul><li>… </li></ul></ul>
  34. 34. Strategies for Validation of KaSPAR Hydrologic Measurements <ul><li>Inundation Extent: </li></ul><ul><li>Map inundation extent using both KaSPAR and the high-resolution Digital Cirrus Camera (DCS) that will be included on AirSWOT. </li></ul><ul><li>The DCS will collect data at spatial resolutions of 50 cm – 1 m. It will include a near-infrared band, which will be ideal for mapping inundation. </li></ul><ul><li>Additionally, cross-river transects of inundation extent will be surveyed in the field using traditional surveying techniques. </li></ul>Map of water-land interface pixels for the Tanana River, Alaska At each red pixel, there is potential for classification error in KaSPAR data. Digital Cirrus Camera to be included on AirSWOT Viewgraph credit: Tamlin Pavelsky UNC-Chapel Hill

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