Progress in Meeting the Challenges of the RBI Spectral Calibration CALCON 2017

Transcription

1 Progress in Meeting the Challenges of the RBI Spectral Calibration CALCON 2017 James Q Peterson (SDL), Harri Latvakoski (SDL), Greg Cantwell (SDL), James Champagne (SDL), Joel Cardon (SDL) 1 SDL/

2 Abstract This presentation is a follow-on to the Radiation Budget Instrument (RBI) spectral calibration plan presented last year [1]. During the past year SDL has refined the RBI spectral calibration plan and replaced modeled and estimated spectral calibration performance values with chamber-validation-test values collected using the Absolute Cavity Radiometer (ACR) and the spectral reference detector (SRD) [2]. This presentation focuses on the progress, uncertainty estimate updates, and confidence gained over the past year that we will meet the RBI spectral calibration requirements, which are both challenging and critical to overall mission success. 1) Background information on RBI program, instrument, and spectral calibration requirements can be found in last year s presentation, 200 nm to 100 µm, with Extremely Low Uncertainty Requirements: Meeting the Challenges of the RBI Spectral Calibration, Proceedings of the 2016 Conference on Characterization and Radiometric Calibration for Remote Sensing, Logan, UT, Aug ) The SRD was built by Harris and delivered to SDL. It is similar to the RBI flight detector total band in spectral responsivity and performance. 2 SDL/

3 Presentation Outline RBI spectral calibration highlights RSR Test Configurations Fourier Transform Spectrometer (FTS) Chamber and optical paths Configuration details for each system component Chamber validation testing RSR results SRD RSR example Applying Tie Points Covariance matrix based uncertainty with Tie Points applied Uncertainty results Summary and path forward 3 SDL/

4 RBI Spectral Calibration Highlights RSR Predictions Provide to SDL by Harris Key RSR Requirements RSR measurements for each RBI sensor (Total, SW and LW) Must cover the full spectral range (200 nm µm) SW and Total RSR band-integrated uncertainty budget of 0.25% when weighted with a solar irradiance spectrum LW and Total RSR band-integrated uncertainty budget of 0.25% when weighted with a 300 K blackbody spectrum.

5 FTS Spectrometer Details Fourier transform spectrometer covers from 0.35 to 100+ µm Internal Glowbar and Tungsten Halogen sources, external QTH and Xe lamp sources Quartz, KBr, CsI and Mylar beamsplitters HeNe metrology laser Sampling every zero-crossing of the HeNe laser fringes Adjustable spectral resolution Lower resolution requires fewer points (shorter scan length) Used in step scan mode: interferometer is stepped and holds optical retardation position between steps Computer controls all operation One of three similar FTS spectrometers at SDL

6 Calibration Test Composite Layout UUT Location inside Chamber SWRS BENCH FTS 6000 LW CHAMBER LWRS FTS 680 LWDC FTS 680 SWRS Short Wave Radiance Source LWRS Long Wave Radiance Source LWDC Long Wave Direct Couple UUT (RBI, APC or SRD) sequentially view calibration sources using a translation/rotation mount

7 RBI RSR Measurement Configurations FTS Test Configuration Wavelength Coverage [µm] Coupling Optics FTS Hardware Configuration FTS Software Controlled Parameter and Settings Optics.Path SWRS SWRS LWRS LWDC LWDC LWDC Optics.Mirror UV-Mirror.2 Al Optics.Filter.1 HeNe.Blue - - RBI.LW RBI.LW RBI.LW Optics.Filter.2 KG Optics.Window UV-Quartz UV-Quartz KBr Silicon Silicon Silicon FTS.Config.FTS_ID FTS.Config.Path External External Internal Internal Internal Internal FTS.Config.Source Xe lamp QTH lamp MWIR MWIR MWIR MWIR FTS.Config.Ap 2 cm-1 2 cm-1 Open Open Open Open FTS.Config.BS UV-Quartz NIR-Quartz KBr CsI Mylar-6 Mylar-12 FTS.Config.Filter FTS.Config.Filter.2 HeNe.Blue FTS.Settings.Source off off MWIR MWIR MWIR MWIR FTS.Settings.Ap 2 cm-1 2 cm-1 Open Open Open Open FTS.Settings.Res FTS.Settings.Scans FTS.Settings.UDR FTS.Settings.ScanRate FTS.Settings.StepDelay FTS.Settings.Sym Sym Sym Sym Sym Sym Sym Configurations 0 and 2 were eliminated based on cold test results Six configurations cover a spectral range of 0.35 to 110 µm

8 Example: APC Test Configuration 3 (TC3) Average of 4 spectral scans overplotted with standard deviation

9 Uncertainty Sources and Time Scales Time Scale Source or Example Correlation Level Mitigate and/or Quantify Sample-to-sample Scan-to-scan (spectra-to-spectra) Test-to-test (UUT-to-UUT) Static long-term Random noise Johnson noise Bit noise FTS source variability short-term Optical path GN 2 purge FTS source variability long-term Positioning and pointing repeatability of FTS and UUT Optical path cryo-ice contamination Detector non-linearity FTS aliasing at HeNe LWRS integrating sphere nonuniformity Correlation within the localized spectral region of a single scan (spectra) due to interferogram zeropadding and apodization Random scan-to-scan Correlation Spectral within a single scan (spectra) Pseudo-random scan-to-scan Systematic correlation within any test configuration Random between test configurations Systematic correlation spectrally and long-term temporally correlated Collect multiple scans/spectra Mitigate Average spectra Quantify Captured in measurement-covariance matrix Collect multiple scans/spectra Mitigate Average spectra Quantify Captured in measurement-covariance matrix Mitigation Apply Tie Point correction* Quantify UUT collection before and after APC Apply TP correction to measurementcovariance matrix to reduce systematically correlated uncertainty* Mitigation Apply Tie Point correction* Quantify Model effects and create a covariance uncertainty matrix Apply TP correction to measurementcovariance matrix to reduce systematically correlated uncertainty* 9 * Tie Point definition and details are provided later SDL/

10 Requirements Flow-down to Meet RBI RSR Uncertainty Specifications Two important requirements are realized from the previous slide: 1. Uncertainty analysis cannot assume spectral bins are uncorrelated (statistically independent) 2. Systematically-correlated effects in the FTS-measured RSR must be corrected to meet RBI uncertainty requirements The impact of these two requirements are: 1. Covariance matrices will be used for all uncertainty analysis 2. Tie Points will be used to correct systematic correlation effects in the FTS-measured RSR 10 SDL/

11 Tie Points Definitions and Details Tie Points are narrow-band filter measurements transferred directly from the ACR to the UUT (Also LW Tie Points) TPs are SI traceable (through the ACR), highly accurate, measured in test-as-flown conditions and include uncertainty TPs lack spectral resolution and spectral range coverage needed for a complete RSR, which are provided by the FTS

12 Tie Point Correction Overview True RSR Measured RSR (contains systematic baseline and random noise) For demonstration purposes only (values are not to scale) RSR baseline with systematic uncertainty Tie Point locations 12

13 Tie Point Corrections Gain Component Force measured RSR segments through TPs 13

14 Tie Point Corrections Slope Component RSR systematic uncertainty residual Systematic uncertainty growth beyond TPs remains unchanged Spectral locations between the TPs are tapered together using ramped weighting functions 14

15 Tie Point Corrections Random Uncertainties Included Due to random noise in both the RSR and TP measurements, the measured RSR baseline does not pass exactly through the true RSR value at the TP locations Tie Point Measurements with RSR Uncertainty Included Clearly if the RSR systematic and random uncertainty is less than the TP correction uncertainty, the use of TP correction will result in net increase in the overall RSR uncertainty 15

16 RSR Tie Point Corrections Final Results After TP correction, the systematic uncertainty between TPs is drastically reduced, however random uncertainty, with lower overall significance, is added 16 TP correction eliminates the cumulative effect of systematic uncertainties, replacing them with less significant random uncertainties

17 RSR Force RSR through Tie Points - Normalized SRD Spectra - Normalized APC Spectra - Computed SRD RSR * RSR Tie Point - Tie Point Corrected SRD RSR Note: This image is proof-of-concept only, using chamber validation data 17 SDL/

18 RSR Uncertainty Covariance matrices Covariance matrices keep track of uncertainties both systematic and random Covariance matrix is defined as ccoooo RR 1, RR 1 ccoooo RR 1, RR 2 CC RR = ccoooo RR 2, RR 1 ccoooo RR 2, RR 2 R n is the RSR in spectral bin n Fractional uncertainty in integral of spectrum times RSR is uu = PPTT CC RR PP SS 1 Δww 1 ; PP = SS SS ii RR ii Δww 2 Δww 2 ii S n is the Spectral radiance in spectral bin n, w n is the width of spectral bin n Non-zero covariance between spectra bins occurs due to Random noise with zero padding spectra and apodizing spectra close to matrix diagonal Spectrometer repeatability, optical coupling mismatch, non-linearity, diffraction uncertainty Covariance matrices add for independent uncertainties

19 Example: Covariance Matrix Uncertainty - TC3 Without Tie Point Correction Covariance matrix is calculated directly from APC and SRD measurement data SS 1 Δww 1 ccoooo RR 1, RR 1 SS 1 Δww 1 SS 1 Δww 1 ccoooo RR 1, RR 2 SS 2 Δww 2 Matrix shown is = SS 2 Δww 2 ccoooo RR 2, RR 1 SS 1 Δww 1 SS 2 Δww 2 ccoooo RR 2, RR 2 SS 2 Δww 2 TC3 Covariance Matrix Image Prior to TP correction Solar spectrum applied Integrated uncertainty = 0.21% Off-diagonal terms show systematic correlation effects Without TP correction 0.21% uncertainty is unacceptable

20 RSR Uncertainty Predictions Tie Points Included Force the FTS RSR measurements through the Tie Points FF ii = TT mm(ii) ff ii + TT mm ii +1 gg ii RR ii ; TT mm = AA mm SS mm FF ii TTTT cccccccccccccccccc ffffffffff RRRRRR aaaa FFFFFF mmmmmmmmmmmmmmmm ssssssssssssssss rrrrrrrrrrrrrrrrrrrr RR ii FFFFFF mmmmmmmmmmmmmmmm RRRRRR vvvvvvvvvv ffffff iiiiiiiiii ii AA mm TTTT mmmmmmmmmmmmmmmm RRRRRR aaaa tttttt pppppppppp mm SS mm FFFFFF mmmmmmmmmmmmmmmm RRRRRR iiiiiiiiiiiiiiiiiiiiiiii tttt tttttt pppppppppp mm ff mm, gg mm wwwwwwwwwwwwwwwww ffffffffffffffffff, ssssss tttt 1 This significantly reduces the systematic uncertainty accumulation in the RSR However, using RSR Tie Points adds random uncertainty of the Tie Point measurements onto the overall uncertainty. Use of Tie Points is beneficial if there is a net reduction on the overall uncertainty

21 Applying TP Corrections to the Covariance Matrix CCCCCC FF ii, FF jj FFFFFFFFFF RRRRRR cccccccccccccccccccc mmmmmmmmmmmm iiii TTTT cccccccccccccccccc aaaaaaaaaaaaaaaa RRRRRR uuuuuuuuuu FF ii TTTT cccccccccccccccccc ffffffffff RRRRRR aaaa FFFFFF mmmmmmmmmmmmmmmm ssssssssssssssss rrrrrrrrrrrrrrrrrrrr TT 0 AAAAAAAAAAAAAA RRRRRR cccccccccccccccccccc ffffffffffff aaaaaaaaaaaa aaaaaa TTTTTT iiii TTTT bbbbbbbb SSSSSSSSSSSS RRRRRR tttt mmmmmmmmm TTTT vvvvvvvvvvvv cccccccccccccccc rrrrrrrrrrrrrrrr tttt aaaaaaaaaaaaaaaa CCCCCC RR ii, RR jj CCCCCCCCCCCCCCCC UUUUUU aaaaaa AAAAAA cccccccccccccccccccc mmmmmmmmmmmmmmmm iiii uuuuuuuuuu oooo RR RR ii FFFFFF mmmmmmmmmmmmmmmm RRRRRR vvvvvvvvvv ffffff iiiiiiiiii ii AA mm TTTT mmmmmmmmmmmmmmmm RRRRRR aaaa TTTT mm SS mm FFFFFF mmmmmmmmmmmmmmmm RRRRRR iiiiiiiiiiiiiiiiiiiiiiii tttt TTTT mm TT mm RRRRRR cccccccccccccccccccc ffffffffffff aaaa TTTT mm RR ii NNNNNNNNNNNNNN ttttttttt vvvvvvvvvv oooo FFFFFF mmmmmmmmmmmmmmmm RRRRRR ffffff iiiiiiiiii ii SS mm(ii) NNNNNNNNNNNNNN FFFFFF mmmmmmmmmmmmmmmm RRRRRR vvvvvvvvvv aaaa TTTT mm ii CCCCCCCCCCCCCCCC ffffffff ssssssssssss ffffff oooo FFFFFF mmmmmmmmmmmmmmmm RRRRRR aaaa TTTT mm ii mm ii LLLLLLLLLLLLLLLL oooo TTTT pppppppppppppppppp iiiiiiiiii ii ssssssssssssss iiii wwww oooo rrrrrr ssssssss mm ii + 1 LLLLLLLLLLLLLLLL oooo TTTT ffffffffffffffffff iiiiiiiiii ii llllllllllll iiii wwww oooo bbbbbbbb ssssssss

22 Example: Covariance Matrix Uncertainty - TC3 Tie Point Correction Applied TC3 Covariance Matrix Image TP correction applied Solar spectrum applied Integrated uncertainty = 0.07% Off-diagonal systematic correlation effects have been reduced Random components are now observable down the matrix diagonal With Tie Point correction applied 0.07% is acceptable!

23 Current RBI RSR Uncertainty Estimates Uncertainty values were computed using the RBI total-band SW-band solar integral uncertainty will be similar to the total-band LW-band 300K BB integral uncertainty will be similar to the total-band Uncertainty in integrated RSR weighted by solar spectrum TC % TC % TC % RSS 0.122% Uncertainty in integrated RSR weighted by 300K blackbody TC % TC % TC % TC % RSS 0.184% 23 SDL/

24 Summary and Path Forward SDL has created and updated an RSR plan that will meet the RBI system requirements Current best estimates indicate that SDL will meet the RSR uncertainty requirements Original RSR modeling values have been replaced with measurement values from chamber validation testing RSR uncertainty modeling will be maintained and updated going forward EDU testing will allow SDL to further refine the uncertainty model Final uncertainty values will be derived from flight-unit testing 24 Thanks to Harris and NASA Langley for supporting this effort SDL/