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Unified Onboard Processing and Spectrometry

Unified Onboard Processing and Spectrometry. Murzy Jhabvala (550) Sarath Gunapala (JPL) Peter Pilewskie (Ames). PI: Si-Chee Tsay (913). Michael King (900) Warren Wiscombe (913) Peter Shu (553) Pen-Shu Yeh (564). Prologue.

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Unified Onboard Processing and Spectrometry

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  1. Unified Onboard Processing and Spectrometry Murzy Jhabvala (550) Sarath Gunapala (JPL) Peter Pilewskie (Ames) PI: Si-Chee Tsay (913) Michael King (900) Warren Wiscombe (913) Peter Shu (553) Pen-Shu Yeh (564) IIP Proposal Summary

  2. Prologue Remote sensing in the Earth sciences has grown remarkably over the last decade. This growth has been spurred by remarkable advances in technology... Of these advances, the merging of spectroscopy and imaging has been the most important. Spectroscopy has been used as a quantitative tool in the laboratory for many years and there exists a wealth of understanding and analysis strategies for such data. Although early imaging spectrometer instruments suffered through the usual development problems, these systems are now approaching the spectral resolution and quality of laboratory measurements, blurring the distinction between the two but also bringing some of the most advanced laboratory spectral analysis techniques to bear on complex Earth science problems. The most advanced sensors and instruments are currently mounted on aircraft, but there are exciting plans to integrate the best of these into orbiting platforms which will facilitate greater accessibility and wider geographic coverage. Remote Sensing for the Earth Sciences: Manual of Remote Sensing, 3rd ed., Vol. 3, A. Rencz, ed., Ch. 5 IIP Proposal Summary

  3. Proposed Activities • Select a combination of “dumb” (proximate differencing) and physics-based lossless spectral compression algorithms for shortwave spectra that will be widely accepted within the community • Develop custom chips for onboard processing of spectrometer data using those algorithms • Integrate those chips into: • Leonardo Airborne Simulator • Quantum Well Infrared Photometer • Conduct flight validation tests IIP Proposal Summary

  4. Why is onboard compression needed? • Data rate! • think of MODIS; then, multiply by 10+ • Generic spectrometer data rate • 1Kx1K 12-bit image, 200 wavelengths = 2.4 Gb • one such image every 100 km (14 s) => 170 Mb/s • total data in 94-min orbit: 1 Tb • 10-min download requires 1.6 Gb/s (ultra-high rate) • The “archive all the raw bits” paradigm has reached the end of its utility (EOSDIS x 10?) IIP Proposal Summary

  5. AVIRIS Image Cube Shows the Problem: Firehoses of Data IIP Proposal Summary

  6. What is Compression, Really? • Just a way of “flattening” a data object • A grey or flat object compresses perfectly • A spectrum with only a few mild ripples is much more compressible than one with big variations...so, get rid of the variations! • Think of it as removing known information • model spectra, lab spectra, empirical spectra... • why send known information to ground 1B times? IIP Proposal Summary

  7. How to Compress? • using a priori knowledge; divide out • extraterrestrial solar spectrum • known absorption spectra • known scattering spectra (e.g. Rayleigh) • use current knowledge • e.g. divide by spectra contiguous in space or time • MPEG, HDTV have pioneered this road • principal components • best: combinations of both strategies IIP Proposal Summary

  8. How to Compress in Hardware? • ASIC: Application Specific Integrated Circuit • FPGA: Floating Point Gate Array • Pen-shu Yeh/553 designed a JPEG ASIC • Code 935 is studying image navig’n using FPGA’s • DoD is now coding numerical methods like tridiagonal solvers into ASIC’s and FPGA’s • This technology has come of age! • Onboard processing is a big NASA goal, but no one has done much about it yet. IIP Proposal Summary

  9. Candidate Spectrometers • Leonardo Airborne Simulator (Tsay/Shu) • single array detector, 0.4 to 5 microns—a first! • operational: aircraft version flew in SAFARI 2000 • Quantum Well Infrared Photodetector (Jhabvala) • the thermal IR, in chunks (3-5, 8-10, 10-12, 14-16 mm) • operational: aircraft version IIP Proposal Summary

  10. 80° FOV 18” 13.5° FOV Leonardo Airborne Simulator 2x16 ch. A/D converters 14 bits, 2MHz 10 frame/sec 4x8 ch. pre-amps dewar computer data storage 4x 26 GB detector/optics module SAFARI-2000 South Africa OR

  11. The Heart of Leonardo Airborne Simulator: ALADDIN Array Detector • ALADDIN astronomical-quality 1024 x 1024 InSb detector; high quantum efficiency in 0.4–5.5 µm. IIP Proposal Summary

  12. 0.4 - 2.5 µm Leonardo Spectrometer for Space 90º FOV wedge filter 1K x 1K InSb array detector @ 50 Kelvin or, 2K x 2K HgCdTe array detector @ 150 Kelvin IIP Proposal Summary

  13. QWIP Airborne Spectrometer • Quantum Well Infrared Photodetector • 256 x 256 GaAs detector array @ 65K • 9° FOV • 16 Hz frame rate • programmable integration time • calibration: cold and hot blackbody sources in lab Flies on Aerocommander (10 km ceiling) IIP Proposal Summary

  14. Quantum Well Infrared Photodetectors IIP Proposal Summary

  15. QWIP Optical Layout IIP Proposal Summary

  16. QWIP as Deer Detector The deer is over 100 m away and not visually discernible. IIP Proposal Summary

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