Apr 10, 2001IIP Proposal Summary 1 Unified Onboard Processing and Spectrometry Murzy Jhabvala (550) Sarath Gunapala (JPL) Peter Pilewskie (Ames) Michael King (900) Warren Wiscombe (913) Peter Shu (553) Pen-Shu Yeh (564) PI: Si-Chee Tsay (913)

Apr 10, 2001IIP 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

Apr 10, 2001IIP 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

Apr 10, 2001IIP 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?)

Apr 10, 2001IIP Proposal Summary 5 AVIRIS Image Cube Shows the Problem: Firehoses of Data

Apr 10, 2001IIP 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?

Apr 10, 2001IIP 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

Apr 10, 2001IIP 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.

Apr 10, 2001IIP 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,  m) –operational: aircraft version

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

Apr 10, 2001IIP Proposal Summary 11 ALADDIN astronomical-quality 1024 x 1024 InSb detector; high quantum efficiency in 0.4–5.5 µm. The Heart of Leonardo Airborne Simulator: ALADDIN Array Detector

Apr 10, 2001IIP Proposal Summary µm or, 2K x 2K HgCdTe array 150 Kelvin 1K x 1K InSb array 50 Kelvin 90º FOV wedge filter Leonardo Spectrometer for Space

Apr 10, 2001IIP Proposal Summary 13 –Quantum Well Infrared Photodetector –256 x 256 GaAs detector 65K –9° FOV –16 Hz frame rate –programmable integration time –calibration: cold and hot blackbody sources in lab Flies on Aerocommander (10 km ceiling) QWIP Airborne Spectrometer

Apr 10, 2001IIP Proposal Summary 14 Quantum Well Infrared Photodetectors

Apr 10, 2001IIP Proposal Summary 15 QWIP Optical Layout

Apr 10, 2001IIP Proposal Summary 16 The deer is over 100 m away and not visually discernible. QWIP as Deer Detector