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VIS-SPEAR Calibration Update

VIS-SPEAR Calibration Update. Prepared for Air Force Research Laboratory AFRL/VS. Aerodyne Research, Inc. 45 Manning Road Billerica, MA 01821-3976 12 March 2002. Agenda. VIS SPEAR Status – Calibration and Early Retrieval Examples Jones (45) VMP Calibration Procedures? Fetrow (15)

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VIS-SPEAR Calibration Update

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  1. VIS-SPEAR Calibration Update Prepared forAir Force Research LaboratoryAFRL/VS Aerodyne Research, Inc. 45 Manning Road Billerica, MA 01821-3976 12 March 2002

  2. Agenda • VIS SPEAR Status – Calibration and Early Retrieval Examples Jones (45) • VMP Calibration Procedures? Fetrow (15) • MODTRAN 4-P Validation Status Conant (45) • Feedback on the MODTRAN 4-P Validation Plan and Implementation Fetrow (15) • Coordinated Measurements for VIS SPEAR and VMP at KAFB? All (15) • Multiple Objectives • Other Sensors: Research Scanning Polarimeter; AERONET Cimel • Anticipated Schedule • LWIR SPEAR Status Scott (15)

  3. Meta-Agenda • Recently achieved key SPEAR-TIP/PolTran milestones: • VIS-SPEAR is now working & field-worthy • VIS-SPEAR is spectro/polar/radiometrically calibrated • We are retrieving Stokes spectrum • Remote Surface Orientation Measurement (RSOM) patent submitted • PolTran validation plan & results synergistic w/ NASA effort • ~ $50K funded ARI effort remaining; additional $50K funded ARI set-aside for “field test” Where-To From Here?

  4. Where-To From Here? • We ask both (1) for optimally directing remaining funds, and (2) to anticipate prospective efforts • Possible Paths • VIS-SPEAR field collects - • Targets; surfaces • Atmospherics (IAW PolTran validation plan) • Likely NASA synergy • PolTran aerosol parametric sensitivity determination • RSOM exploitation for target discrimination • (XX)IR-SPEAR? Can we discuss (our roles in) AFRL SpectroPolarimetry Roadmap?

  5. Recent & Prospective Progress • We demonstrated calibrated “narrowband” (~14nm resolution) polarimetry against data. • VIS-SPEAR is ready for local field data collects (FEB02) • Steps remaining for VIS-SPEAR readiness for field test campaigns: • Improve mounting (CNC table too cumbersome) • Refine calibration; test against independent calibration standards • Devise field-deployable calibration apparatus (existing lab standard too cumbersome) • Integrate calibration/Stokes retrieval into data acquisition program

  6. Fringe Image

  7. Fringe Spectra Developed utility for real-time display of fringes to align sensor

  8. SPEAR/AERONET Correlative Experiments • Perform measurements with VIS-SPEAR and AERONET photometer collocated to assess radiometric and polarimetric performance of VIS-SPEAR. • AERONET photometers have a long legacy (since 1993) and well planned calibration program. • Experiment serves the interests of both AFRL and NASA.

  9. Cimel Robotic Photometer • Direct solar and sky radiance measurements. • Sunrise to sunset. • Solar principal planes and solar almucantars. • 8 pos. filter wheel w/ 4 interference filters. Additional 3 for polarization at 870 nm. • Satellite feed and automatic data processing available via web. • Rigorous calibration plan.

  10. VIS-SPEAR Field Mounts • Scans performed manually: • Almucantars: VIS-SPEAR mounted on heavy duty tripod Alt-Az head w/ graduations. • Principal Planes: VIS-SPEAR mounted on equatorial telescope mount adjusted for operation at 0 deg latitude. • Scans performed automatically: • Full imagery: VIS-SPEAR mounted on CNC rotary table. Very bulky – needs to be replaced for future field measurements.

  11. Sensor Comparison

  12. VIS-SPEAR

  13. Cimel Photometer

  14. SPEAR/CIMEL DoLP

  15. VIS-SPEAR DoLP

  16. AERONET Polarimetry

  17. Retrieval Context • Retrieve Stokes spectrum from x(i) • x(i) is output of i-th pixel • Sensor input Stokes vector S(l). • Gaussian spectral blur h(l), gain R(l), and offset C(i). • Mueller matrix M; P-SIM crystals (lengths and birefringence of material). Integration “over blur” – x(i) includes tails of x(i-1) and x(i-1). • Retrieval first requires estimation of system parameters

  18. Calibration Sequence • Cal Sequence - designed to estimate parameters of the system equation • Spectral cal: • Mapping between wavelength vs. pixel index; • Spectral blur h(l). • NUC (Non-Uniformity Correction): • R and C • Retardance cal: • L1, L2, Dn[l] • and any additional system retardance

  19. Spectral Cal • Infer from spectral line source images: • wavelength vs. pixel index; blur {h[] and s} • Hg(Ar) and Kr vapor lamps • line widths << pixel bin • Non-linear regression using multiple lines: • retrieves: quadratic polynomial mapping between l and pixel index I; and s (gaussian blur) NLR retrieval matched the Andor and slit blur estimates pixel bin: 2.3nm

  20. Non-Uniformity Correction (NUC) Slit l • NUC accounts for: • Spatial non-uniformity of pixel gain & offset • Equalization of aperture shading (Cos4), spectral transmittance • Maps raw digital counts to radiance units • Requires spectrally-calibrated sources • Unlike conventional 2D imaging flat-fielding

  21. Retardance Cal • Global non-linear regression retrieves from known input Stokes spectra (“Charlie Brown” frames): • crystal lengths L1, L2, quadratic polynomial Dn[l]; • nuisance parameters (for the calibration itself): • i0 (intensity scale) • raop (unknown polarizer alignment offset angle) • Employs Labsphere source (known spectral intensity) and rotating polarizer • absolute polarizer rotation alignment presently unknown - known relative rotations between frames • assumes perfect, spectrally flat polarizer

  22. Retardance Cal l Highly non-smooth error surface requires Global NLR • The objective (error) function for global NLR: • sum of squared errors: • error=data vs. parametric signal model • Model parameters are L1, L2, Dn[l], i0, raop Error surface vs. crystal length parameters L1 and L2 Nominal vs. fitted polynomial Dn[l]

  23. Retardance Cal l • Excellent model fit (calibration), except at short wavelength end for sideband-rich AoPs • Fit error consistent with NUC, other errors ~1-2% (for now) AoP=136deg Data Model AoP=6deg

  24. Stokes Retrieval Strategy • Invert the system equation • linear (pseudoinverse-”PI”) for Stokes parameters • assumes spectrally-constant source across Dl • non-linear regression (“NLR”) for: • spectrally-constant {I,dop,aop,d} across Dl • parametric spectral source models (Sellmeier, Lorentz) • requires global solver

  25. Stokes Retrieval to Date l • 6-sample Dl (~14nm) Stokes retrieval achieved from PseudoInverse and NLR • Assuming flat source spectum over 14nm band • But works nonetheless against blackbody-like spectrum • Handling spectral structure: • Will try NLR against spectral models • Actual implementation: basis pursuit? AoP=136deg Data Model AoP=6deg

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