1. 1 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

2. 2 Agenda VIS SPEAR Status – Calibration and Early Retrieval Examples Jones (45) VMP Calibration Procedures? Fetrow (15) MODTRAN 4-P Validation StatusConant(45) Feedback on the MODTRAN 4-P Validation Plan and ImplementationFetrow (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 StatusScott (15)

3. 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. 4 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. 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. 6 Fringe Image

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

8. 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. 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. 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. 11 Sensor Comparison

12. 12 VIS-SPEAR

13. 13 Cimel Photometer

14. 14 SPEAR/CIMEL DoLP

15. 15 VIS-SPEAR DoLP

16. 16 AERONET Polarimetry

17. 17 Retrieval Context Retrieve Stokes spectrum from x(i) –x(i) is output of i-th pixel –Sensor input Stokes vector S( ). –Gaussian spectral blur h( ), gain R( ), 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. 18 Calibration Sequence Cal Sequence - designed to estimate parameters of the system equation –Spectral cal: Mapping between wavelength vs. pixel index; Spectral blur h( ). –NUC (Non-Uniformity Correction): R and C –Retardance cal: L1, L2,  n  and any additional system retardance

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

20. 20 Non-Uniformity Correction (NUC) NUC accounts for: –Spatial non-uniformity of pixel gain & offset –Equalization of aperture shading (Cos 4 ), spectral transmittance –Maps raw digital counts to radiance units Requires spectrally-calibrated sources –Unlike conventional 2D imaging flat-fielding Slit

21. 21 Retardance Cal Global non-linear regression retrieves from known input Stokes spectra (“Charlie Brown” frames): –crystal lengths L1, L2, quadratic polynomial  n  –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. 22 Retardance Cal Nominal vs. fitted polynomial  n  The objective (error) function for global NLR: –sum of squared errors: –error=data vs. parametric signal model –Model parameters are L1, L2,  n , i0, raop Error surface vs. crystal length parameters L1 and L2 Highly non-smooth error surface requires Global NLR

23. 23 Retardance Cal 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=6deg AoP=136deg Data Model

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

25. 25 Stokes Retrieval to Date 6-sample  (~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=6deg AoP=136deg Data Model