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Staggered PRT Update

Staggered PRT Update. Sebastián Torres CIMMS/NSSL. Technical Interchange Meeting Spring 2008. Staggered PRT Evolution. 1976: Application to weather radars Sirmans, Zrnić, and Bumgarner 1985: Statistical performance Zrnić and Mahapatra. Sebastián NOT thinking about staggered PRT in 1976.

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Staggered PRT Update

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  1. Staggered PRT Update Sebastián Torres CIMMS/NSSL Technical Interchange Meeting Spring 2008

  2. Staggered PRT Evolution • 1976: Application to weather radars • Sirmans, Zrnić, and Bumgarner • 1985: Statistical performance • Zrnić and Mahapatra Sebastián NOT thinking about staggered PRT in 1976

  3. Staggered PRT Evolution (II) • 1999: Spectral clutter filter • NSSL Report 3 • 2003: AEL with simpler DC removal clutter filter • NSSL Report 7 • 2005: AEL with complex spectral clutter filter • NSSL Report 9

  4. Test VCPs for Staggered PRT • 2007: Staggered PRT subcommittee • Two test VCPs based on VCP 12 • Intermediate and high elevations running SPRT (k = 2/3) • New PRT set to optimize SPRT performance • ra,D > min(rmax , 230 km) • VCP 14: Same dwell times as VCP 12 • VCP 15: Double dwell times as VCP 12 for SPRT

  5. 2008 AEL Updates • Re-ordered steps • Combined powers computed at an earlier stage • Short/long PRT order irrelevant • Generalized velocity dealiasing rules • Old AEL only handled 2/3 PRT ratio • Ground clutter filter • New description matches RVP8’s implementation • Spectrum width computation • Overlaid echo determination • Removed legacy features • Range averaging of reflectivity • Formatting for all moments Sebastián thinking about staggered PRT in 2008

  6. April 2008 SPRT AEL 1. Pre-computation of velocity de-aliasing rules For each range bin n, where 0 < n < max(N1,N2) 2. Clutter filtering 3. Power and correlation computations for each PRT End 4. Short/long PRT data swap For each range bin n, where 0 < n < N2 5. Combined power computation End 6. Strong point clutter canceling For each range bin n, where 0 < n < N2 7. Signal power computation 8. Reflectivity computation 9. Velocity computation 10. Spectrum width computation 11. Determination of significant returns for reflectivity 12. Determination of significant returns for velocity 13. Determination of significant returns for spectrum width End For each range bin n, where 0 < n < N2 14. Determination of overlaid returns for velocity and spectrum width End

  7. Velocity Dealiasing Updates • 2003 AEL • Only supported 2/3 PRT ratio • This constraint is not necessary if using DC removal for clutter filtering • k = 2/3 leads to a minimum number of dealiasing rules in the VDA • This constraint is necessary if using SACHI • Best performance for clutter filtering and spectral processing • 2008 AEL • Supports any PRT ratio • Other PRT ratios may prove useful

  8. Velocity Dealiasing v1 - v2 True velocity v2 ^ add 2va1 to v1 va2 closest level ^ ^ v1 – v2 • v1 and v2 are estimated from short and long PRT pairs • A velocity difference transfer function determines the intervals for the different dealiasing rules Aliased v v1 va1 True v

  9. Velocity Dealiasing Rules • Simple recursive algorithm to generate dealiasing rules (Torres et al. 2004) • PRT ratio = 2/3 (5 rules) • PRT ratio = 3/5 (7 rules) • Values are normalized by the extended Nyquist velocity, so these can be pre-computed for any given PRT ratio

  10. Velocity Dealiasing • Find the closest VDTF constant to v1 – v2 • Use the corresponding dealiasing factor (P) to dealias v1 to the “correct” Nyquist co-interval • v = v1 + 2va1P • A “catastrophic error” occurs if errors of estimates are such that v1 – v2 is pushed closer to the wrong VDTF constant • These appear as speckles in the velocity fields

  11. “Catastrophic” Velocity Errors • Catastrophic errors are more likely for wider spectrum widths • A velocity dealiasing algorithm based on spatial continuity can be used to mitigate these

  12. “Catastrophic” Velocity Errors

  13. April 2008 SPRT AEL 1. Pre-computation of velocity de-aliasing rules For each range bin n, where 0 < n < max(N1,N2) 2. Clutter filtering 3. Power and correlation computations for each PRT End 4. Short/long PRT data swap For each range bin n, where 0 < n < N2 5. Combined power computation End 6. Strong point clutter canceling For each range bin n, where 0 < n < N2 7. Signal power computation 8. Reflectivity computation 9. Velocity computation 10. Spectrum width computation 11. Determination of significant returns for reflectivity 12. Determination of significant returns for velocity 13. Determination of significant returns for spectrum width End For each range bin n, where 0 < n < N2 14. Determination of overlaid returns for velocity and spectrum width End

  14. Clutter Filtering Updates • 2003 AEL: DC removed from auto-covariances • Filtered power Time Series ComputeMean |.|2 Filtered Autocovariance - Compute Autocovariance + Autocovariance

  15. Clutter Filtering Updates (II) • 2008 AEL: DC removed from time series • Filtered power Time Series ComputeMean Filtered Time Series Filtered Autocovariance - Compute Autocovariance +

  16. Clutter Filtering Updates (III) • Are the old and new DC removal filters the same?

  17. GCF Performance Old AEL – GCF ON New AEL – GCF OFF New AEL – GCF ON New AEL – GCF ON SACHI Filter

  18. April 2008 SPRT AEL 1. Pre-computation of velocity de-aliasing rules For each range bin n, where 0 < n < max(N1,N2) 2. Clutter filtering 3. Power and correlation computations for each PRT End 4. Short/long PRT data swap For each range bin n, where 0 < n < N2 5. Combined power computation End 6. Strong point clutter canceling For each range bin n, where 0 < n < N2 7. Signal power computation 8. Reflectivity computation 9. Velocity computation 10. Spectrum width computation 11. Determination of significant returns for reflectivity 12. Determination of significant returns for velocity 13. Determination of significant returns for spectrum width End For each range bin n, where 0 < n < N2 14. Determination of overlaid returns for velocity and spectrum width End

  19. Spectrum Width • Implemented legacy estimator based on ratio of lag-0 to lag-1 autocorrelations • Design alternatives • R0: short PRT, long PRT, or combined? • R1: short PRT or long PRT? • Six variations • Considerations • Errors of estimates • Saturation

  20. Spectrum Width Errors Solid lines: short (or long) PRT pulses for power Dashed lines: all pulses for power Lines without markers:short PRT pairs for autocorrelation Lines with markers:long PRT pairs for autocorrelation SNR = 40 dB DT = 60 msk = 2/3

  21. Spectrum Width Updates T2 T1 • 2003 AEL • Legacy R0/R1 estimator • R0 comes from long PRT pulses • R1 comes from long PRT pairs • 2008 AEL • Legacy R0/R1 estimator • R0 comes from all pulses • Reduced errors for Segment II • R1 comes from short PRT pairs • Larger saturation value I II I II III

  22. April 2008 SPRT AEL 1. Pre-computation of velocity de-aliasing rules For each range bin n, where 0 < n < max(N1,N2) 2. Clutter filtering 3. Power and correlation computations for each PRT End 4. Short/long PRT data swap For each range bin n, where 0 < n < N2 5. Combined power computation End 6. Strong point clutter canceling For each range bin n, where 0 < n < N2 7. Signal power computation 8. Reflectivity computation 9. Velocity computation 10. Spectrum width computation 11. Determination of significant returns for reflectivity 12. Determination of significant returns for velocity 13. Determination of significant returns for spectrum width End For each range bin n, where 0 < n < N2 14. Determination of overlaid returns for velocity and spectrum width End

  23. Overlaid Censoring • Algorithm assumes that echoes do not extend beyond ra2 • Echoes that extend beyond ra1 are overlaid in every other pulse • Use segment I powers from short PRT pulses and segment III powers from long PRT pulses to determine overlaid echoes T1 T2 I II I II III

  24. Overlaid Censoring Rules T1 T2 • Segment I (some purple) • Unrecoverable if P1(n) < P2(n + N1) + Tov • Should we ignore non-significant returns? • P1(n) < P2(n + N1) + TovANDP2(n + N1) > NOISE + TSNR • Segment II (no purple) • No unrecoverable echoes • Segment III (all purple) • All unrecoverable I II I II III

  25. Overlaid Censoring in Action • Segment I 0 km < r < 92 km • Segment II 92 km < r < 184 km • Segement III 184 km < r < 276 km Segment III Segment II Segment I Data collected with KOUN on March 18, 2003

  26. Overlaid Censoring Strict overlaid determination Legacy overlaid determination Which one do we prefer? P1(n) < P2(n + N1) + Tov P1(n) < P2(n + N1) + TovANDP2(n + N1) > NOISE + TSNR

  27. Validation • ROC implemented staggered PRT algorithm like in 2008 AEL without generalized dealiasing rules • We’re currently validating this implementation ROC NSSL

  28. Conclusions • NSSL and ROC designed new test VCPs based on staggered PRT for the ORDA • NSSL provided a new AEL for staggered PRT with updates in the following areas: • Re-ordering of steps • Generalized velocity dealiasing rules • Ground clutter filtering • Spectrum width estimation • Overlaid censoring rules • NSSL and ROC are validating the ORDA implementation of staggered PRT

  29. Questions? Staggered PRT(k = 2/3, same DT) Batch ModeVCP 11 March 3, 20042.5 deg ra = 147 km, va = 28.8 m/s ra = 184 km, va = 45.1 m/s

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