1. End of Semester Meeting Conically Scanning Active/Passive Sensor Simulation Tool (CAPS) Pete Laupattarakasem Liang Hong

2. Presentation Outline  CAPS Overview  Module Descriptions  Simulation Improvements  Results & Verification  Future Work & Summary

3. CAPS Overview  CAPS is a computer simulation aimed to simulate space borne conically scanning radar  Cover end-to-end mission operation  Define orbit/sensor/beam parameters  Simulate realistic environment  Retrieve geophysical parameters  Active Sensor (Scatterometer)  Wind  0 calculations  Passive Sensor (Radiometer)  Rain effects  Future simulation include T b contributions from rain effects

4. Current Phase  Simulate SeaWinds on QuikSCAT measurement over oceans  Rain-free simulation  Verify wind retrieval result with compass simulation  Performance test of wind retrieval algorithm  Compass simulation assigns known wind field and compares with retrieved wind vectors  WS = 5, 10, 20 ms  Wind Dir = 0, 30, 60 … 330   Noise-free and noisy  Run whole mission  ECMWF serves as wind field surface truth

5. CAPS Structure  CAPS architecture  MATLAB  Main program (GUI) calls subroutine m-Files  Fast matrix calculations  User friendly and easy output displays  Fortran (WRET subroutine in Wind Retrieval )  Computation intensive task, efficient loop calculations CAPS GEOMETRYINTERPOLATIONGROUPING WIND RETRIEVAL Calculate lat/lon of center IFOV from user-defined inputs Interpolate model wind field for each IFOV Group measurement according to given wind cells Retrieve wind measurements

6. Simulation Block Diagram Interpolate Geophysical Parameters (T b, wind vector, rain rate) Calculate Microwave Sensor Observables Geophysical Retrieval Satellite Orbit Geometry Calculation Model Geophysical Parameters Compare Geophysical Parameters and Calculate Statistics Group Measurements User Inputs Geom. Interpolation Wind Ret. Grouping ECMWF

7. Presentation Outline  CAPS Overview Module Descriptions  Simulation Improvements  Results & Verification  Future Work & Summary

8. Geometry Module  Orbital Inputs  Start/stop point (lat/lon)  Height  Sensor Inputs  Scan rate  Overlapping factor  Frequency, pulse length  Beam Parameters  Beam angles (cone, HPBW angles)  Polarization  Calculates lat/lon of center of IFOV with curved earth geometry based on user-defined inputs

9. Footprint & Flavors Perform 360  conical scan Inclination angle = 98.61  Forw-V Forw-H Aft-V Aft-H Scan direction 1800 km 1400 km

10. Geometry Output Example Geo. Foot printMeasurements in ¼  box Start point Ran from -40  to 40  lat Set as 50% overlapping (az)

11. Interpolation Module  Load ECMWF model wind vector and interpolate to IFOV points calculated by Geometry Module  Rain effects   T b due to rain rate   0 due to rain volume backscatter  Atmospheric attenuation due to averaged monthly climatology and rain contamination.  Land and ice masks are applied  Antenna pattern convolution is the most time consuming part

12. Grouping Module  Assign WVC index to each entry  Group measurements into user-defined cell size  SeaWinds cell box = 0.25  x0.25   Approximately 10-14 measurements in a box  The least time consuming module

13. Wind Retrieval (WRET)  Assign  0 to grouped wind vectors  0 tot =   0 wind +  0 rain  0 wind is from Geophysical Model Function (GMF)  0 rain is delta NRCS due to rain volume backscatter  is atmospheric + rain attenuation  Random noise can be added at user preference  MLE:  Rank wind vectors with MLE values  Select the one closest to the truth

14. Presentation Outline  CAPS Overview  Module Descriptions Simulation Improvements  Results & Verification  Future Work & Summary

15. Simulation Improvements GeometryInterpolationGroupingWind Retrieval Misfunctions Desc. pass Negative  handling Cell size factorFlavors selection Desc. azimuth correction Array index error in averaging winds in one cell Flavors Wind vector candidate sorting (infinity loop) Improvements Substitute “For loops” by matrix cell calculation Add overlap factor WRET fine search step size Add true azimuth, substitute pol-index with flavor# Wind vector selection (based on smallest Euclidean distance to truth)

16. Major Fixes (1)  Negative  handling  Improper method using “mod” 4 flavors 3+ flavors CorrectedWrong

17. Major Fixes (2)  Flavor Selection  Previously, # of records were counted instead of # of flavors  With flavor records introduced from Geometry module, flavors can be sorted instantly  “For” loops substitutions  MATLAB is good at matrix calculations in stead of loops  Reduce execution time by the factor of 10+  E.g. in grouping, from >20 mins. to <2 mins  More work to do in antenna convolution

18. Presentation Outline  CAPS Overview  Module Descriptions  Simulation Improvements Results & Verification  Future Work & Summary

19. Case Description  Geometry is run from  -40 to 40 degrees in Lat.  220 degrees in Lon.  Ascending pass orbit  50% overlap in cross track scanning  Over 50,000 measurements made, ~ 13,000 WVC’s after grouped

20. Compass Simulation Results (Noise-free) WS = 5 m/sWind Dir = 120 deg Mean = 4.98 STD = 0.01 Mean = 119.98 STD = 1.28

21. Compass Simulation Results (Noisy) WS = 5 m/sWind Dir = 120 deg Mean = 4.98 STD = 0.28 Mean = 120.22 STD = 13.49

22. WRET: Results in scatter plots

23. WRET: Results in histograms

24. Presentation Outline  CAPS Overview  Module Descriptions  Simulation Improvements  Results & Verification Future Work & Summary

25. Future Works  Code Optimization  Crucial  ‘Out of memory’ when runs antenna pattern convolution. Code needs modification  Performance enhancement  Reduce loops  More MATLAB built-in functions  Verify More Cases  Ascending, descending  With/without noise  Incorporate More Features  Rain effect  New RadTb algorithm in Interpolation Module

26. Work Summary & Conclusion  Code Debugging  Crucial Errors  Algorithm logics  Incompatibility in parameter transferring  Improper parameter treatment  Performance Improvements  Add more user interface parameter  Preserve useful parameters (for verification)  Replace loop and redundant calculations  More bugs expected!  CAPS is a powerful spaceborne radar simulation tool

27. Back Ups

28. WRET: Low Wind (0~5m/s)

29. WRET: Mid Wind (5~10m/s)

30. WRET: High Wind (10~15m/s)