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Real-time Monitoring of Uncertainty due to Refraction in Multibeam Echosounding

Real-time Monitoring of Uncertainty due to Refraction in Multibeam Echosounding. J. Beaudoin Ocean Mapping Group University of New Brunswick. 1450 m/s. 1500 m/s. Introduction. CSL Heron. CCGS Creed. CCGS Matthew. CCGS Amundsen. Assessing Refraction Artifacts in Real-Time.

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Real-time Monitoring of Uncertainty due to Refraction in Multibeam Echosounding

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  1. Real-time Monitoring of Uncertainty due to Refraction in Multibeam Echosounding J. Beaudoin Ocean Mapping Group University of New Brunswick Shallow Survey 2008

  2. 1450 m/s 1500 m/s Introduction CSL Heron CCGS Creed CCGS Matthew CCGS Amundsen Shallow Survey 2008

  3. Assessing Refraction Artifacts in Real-Time • Highly subjective • Requires constant vigil • Can overreact over flat seafloors • Can “underreact” over complicated topography • Impossible for iso-velocity displays (e.g. Reson 81XX display) Shallow Survey 2008 www.reson.com

  4. Depression angle TWTT Investigation depth TWTT Sound speed Depth Proposed Approach:Raytracing Simulation • Isolates raytracing portion of depth reduction procedure: no sounding data required! • Requires accurate model of raytracing procedure: • Draft • Angular sector • Survey depth • Surface sound speed probe 2 1 • Compute common TWTT • Raytrace in test watercolumn • Difference the solutions 3 Depth error Shallow Survey 2008 Horizontal error

  5. Sound speed Depth Application to Real-Time Monitoring “Smile” artifacts near surface Bias cancels out at mid-depth “Frown” artifacts at depth It’s important to see the whole picture Shallow Survey 2008

  6. Sound speed Depth Uncertainty Wedge Error (%w.d.) Shallow Survey 2008

  7. Sound speed Depth Simplification for Real-Time Decision Making 0 - 0.25% w.d. 0.25 - 0.5% w.d. 0.5 - 0.75% w.d. 0.75 - 1.0% w.d. > 1.0% w.d. Shallow Survey 2008

  8. 6 5 vs. 6 5 4 vs. 5 sound speed 6 4 3 vs. 4 5 4 3 2 1 3 depth 2 vs. 3 2 1 vs. 2 1 2 3 4 5 6 depth Snapshots of Refraction Bias Through an Evolving Watercolumn 1 Shallow Survey 2008

  9. 6 5 5- 4 5- 3 sound speed 5 4 4 2 depth 4 1 Time Evolution of Bias Between Casts HUGE ASSUMPTION: Linear growth of bias with time Not unreasonable if you’re sampling at a high rate but DEFINITELY not applicable if you’re undersampling Shallow Survey 2008

  10. Comparison of cast 1 & 2 Comparison of cast 2 & 3 sound speed 3 depth 2 1 Real-Time Uncertainty Visualization Look direction It’s important to be able to visualize the time evolution and history of error Shallow Survey 2008

  11. Uncertainty Visualization Sound Speed Field Depth Bottom Error Analysis Time Uncertainty Field Depth Shallow Survey 2008

  12. Real-Time Monitoring Depth Time Shallow Survey 2008

  13. Other ApplicationsError Analysis with Raytrace Simulation • Pre-survey Analysis • CSL Heron, Port of Saint John (2008) • Quality Assurance • CCGS Matthew, Advocate Bay (2008) • Pre-survey Analysis • CCGS Matthew, EM710 acceptance trials (2005) Shallow Survey 2008

  14. Example 1: CSL Heron, Port of Saint John MVP30 Sound speed Temperature Salinity Shallow Survey 2008

  15. Problem area Sound speed field Casts within problem area highlighted Geographic plot of depth error highlights areas where the watercolumn’s rate of changeexceeds our ability to sample it… Error Field HIGH TIDE Error Field LOW TIDE • How does this affect survey planning? • Less of our angular sector is within tolerable uncertainty, so can reduce line spacing in these areas to maintain accuracy • Could reduce vessel speed to increase spatial sampling of the rapidly changing watermass • Could survey at low tide Shallow Survey 2008

  16. Example 2: Post-SurveyQuality Assurance Bay of Fundy CCGS Matthew - EM710 (140° sector) - MVP200 Sound speed Temperature Salinity Shallow Survey 2008

  17. Error analysis Post-Survey Quality Assurance MVP200 • - 233 casts over 9.5 hr survey, 2 min. sampling interval • Uncertainty due to refraction maintained within +/- 0.02% w.d. !! Shallow Survey 2008

  18. Post-Survey Quality Assurance Cross sectional view of soundings • Refraction uncertainty is noise in the error budge • Largest source of uncertainty is water level • Soundings shown here are tidally reduced with WebTide (2D barotropic hydrodynamic model)… CHS uses GPS/RTK tide Shallow Survey 2008

  19. Example 3: What is oceanographically significant? 2005 CCGS Matthew EM710 Acceptance Trials MVP200 95 casts collected during transit Sound speed casts Only 36 casts required to maintain uncertainty < 0.25% w.d. Shallow Survey 2008

  20. 36 casts required 95 casts collected How’d you do that?? Shallow Survey 2008

  21. The “Goldilocks” Watermass The Oversampled Watermass The “Goldilocks” Watermass 95 casts collected 36 casts required Shallow Survey 2008

  22. Conclusion • Ability to monitor watercolumn conditions as a source of error gives unprecedented control over refraction • Surveyors can have confidence in refraction solution in real-time • The ability to “tune” MVP profile sampling rate can minimize wear on equipment while maintaining a desired accuracy: The Goldilocks Watermass • Many other analysis problems are easily solved using the OMG/UNB SVP Toolkit: Pre-analysis, QA Shallow Survey 2008

  23. Future Work • Incorporation of UNB uncertainty monitoring in ODIM Brooke Ocean MVP controller • Automated MVP deployment with error monitoring & error prediction • Application of simulator to case of undersampled watercolumn Shallow Survey 2008

  24. Acknowledgements • NSERC and CFI funding of ArcticNet NCE • Sponsors of the UNB Chair in Ocean Mapping • U.S. Geological Survey • Kongsberg Maritime • Royal (U.K.) Navy • Fugro Pelagos • Route Survey Office of the Canadian Navy • Rijkswaterstaat • Mike Lamplugh & Jon Griffin, CHS Atlantic • ODIM Brooke Ocean • Students of UNB HydroCamp 2008 Shallow Survey 2008

  25. Shallow Survey 2008

  26. Extra Slides Shallow Survey 2008

  27. Simulation Subtleties • Roll & Pitch • Performance envelope • Along-track slope • Across-track topography Shallow Survey 2008

  28. Surface Sound Speed • Can mimic use of a surface sound speed probe: • Retrieve sound speed at transducer depth from control cast • Use this to compute ray parameter for raytrace with test cast Shallow Survey 2008

  29. Along-track view Step artifact at moment of transition Across-track view Depth difference (m) Predicted difference from raytrace simulator Difference between swaths before and after transition Across-Track (m) Does this actually work??Refraction Step Artifacts Shallow Survey 2008

  30. 6 5 4 3 2 1 What about in between casts? Yes? • Are you stuck with real-time reduced soundings (e.g. REA)? ...or… • Can you post-process using “nearest in time” No? • Hmmmm Depends if you are sampling the watercolumn at a high rate Shallow Survey 2008

  31. sound speed 5 4 depth Interpolation of Error Between CastsCase 1: Stuck with real-time reduced soundings Outer beam depth error 0.81% w.d. 0% w.d. Cast 4 Cast 5 Time • Cast 4 is used up to the moment that cast 5 is acquired • Error is zero at moment just after acquisition of cast 4 • Error increases with time (linearly?), reaching a maximum just prior to collection of cast #5 • Error returns to zero after acquisition of cast 5, increasing until the next cast Shallow Survey 2008

  32. 5- 5 sound speed 5 4+ 4 depth Case 1:Stuck with real-time reduced soundings 4+ Shallow Survey 2008

  33. 0.81% w.d. 0% w.d. 0% w.d. 0.81% w.d. sound speed Interpolation of Error Between CastsCase 2: Will post-process using “nearest in time” 5 4 depth Outer beam depth error tmidpoint t4 t5 Time Shallow Survey 2008

  34. 6 5 4 sound speed 3 5 depth 4 2 1 Case 2:Will post-process using “nearest in time” 5- 4+ Shallow Survey 2008

  35. 5 4+ Case 2:Will post-process using “nearest in time” Error increases with time (linearly?), reaching a maximum at the midpoint between collection of casts 4 & 5; error then decreases with time, reaching a minimum at the moment cast 5 is collected Shallow Survey 2008

  36. Case 1 vs. Case 2 Last observed in time Depth Closest in time Depth Shallow Survey 2008 Time

  37. Case 3: Undersampled Watercolumn • Imprudent to interpolate, BUT… • Snapshot of uncertainty is still a useful metric that can be used to compile an “average” uncertainty • ESS: uncertainty of averages • UNB: average of uncertainties Shallow Survey 2008

  38. sound speed 16 depth 15 Interpolation of Error Between CastsCase 3: Undersampled Watercolumn Interpolate error? Bad idea… Outer beam depth error Cast 15 Cast 16 Time Time 1510 m/s Depth 1450 m/s Imprudent to interpolate, BUT… Snapshot of uncertainty is still a useful metric that can be used to compile an “average” uncertainty Shallow Survey 2008

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