Dr. Michael J. Gazarik Profile

Dr. Michael J. Gazarik

Branch Head, Passive Sensor Systems at NASA Langley Research Ctr

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Publications (10)

Proceedings Article | 13 October 2010 Paper

CLARREO: cornerstone of the climate observing system measuring decadal change through accurate emitted infrared and reflected solar spectra and radio occultation

Stephen Sandford, David Young, James Corliss, Bruce Wielicki, Michael Gazarik, Martin Mlynczak, Alan Little, Craig Jones, Paul Speth, Don Shick, Kevin Brown, Kurtis Thome, Jason Hair

Proceedings Volume 7826, 782611 (2010) https://doi.org/10.1117/12.866353

KEYWORDS: Climatology, Environmental sensing, Observatories, Infrared radiation, Climate change, Spectroscopy, Satellite navigation systems, Calibration, Infrared spectroscopy, Signal detection

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Proceedings Article | 11 December 2008 Paper

Radiometric modeling and calibration of the Geostationary Imaging Fourier Transform Spectrometer (GIFTS) ground based measurement experiment

Jialin Tian, William Smith, Michael Gazarik

Proceedings Volume 7149, 71490C (2008) https://doi.org/10.1117/12.804949

KEYWORDS: Calibration, Staring arrays, Temperature metrology, Spectroscopy, Fourier transforms, Infrared spectroscopy, Infrared imaging, Data modeling, Humidity, Remote sensing

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The ultimate remote sensing benefits of the high resolution Infrared radiance spectrometers will be realized with their geostationary satellite implementation in the form of imaging spectrometers. This will enable dynamic features of the atmosphere's thermodynamic fields and pollutant and greenhouse gas constituents to be observed for revolutionary improvements in weather forecasts and more accurate air quality and climate predictions. As an important step toward realizing this application objective, the Geostationary Imaging Fourier Transform Spectrometer (GIFTS) Engineering Demonstration Unit (EDU) was successfully developed under the NASA New Millennium Program, 2000-2006. The GIFTS-EDU instrument employs three focal plane arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The GIFTS calibration is achieved using internal blackbody calibration references at ambient (260 K) and hot (286 K) temperatures. In this paper, we introduce a refined calibration technique that utilizes Principle Component (PC) analysis to compensate for instrument distortions and artifacts, therefore, enhancing the absolute calibration accuracy. This method is applied to data collected during the GIFTS Ground Based Measurement (GBM) experiment, together with simultaneous observations by the accurately calibrated AERI (Atmospheric Emitted Radiance Interferometer), both simultaneously zenith viewing the sky through the same external scene mirror at ten-minute intervals throughout a cloudless day at Logan Utah on September 13, 2006. The accurately calibrated GIFTS radiances are produced using the first four PC scores in the GIFTS-AERI regression model. Temperature and moisture profiles retrieved from the PC-calibrated GIFTS radiances are verified against radiosonde measurements collected throughout the GIFTS sky measurement period. Using the GIFTS GBM calibration model, we compute the calibrated radiances from data collected during the moon tracking and viewing experiment events. From which, we derive the lunar surface temperature and emissivity associated with the moon viewing measurements.

Proceedings Article | 9 October 2008 Paper

Radiometric and spectral calibrations of the Geostationary Imaging Fourier Transform Spectrometer (GIFTS) using principle component analysis

Jialin Tian, William Smith, Michael Gazarik

Proceedings Volume 7106, 710613 (2008) https://doi.org/10.1117/12.800015

KEYWORDS: Calibration, Staring arrays, Spectroscopy, Temperature metrology, Electronics, Spectral calibration, Satellites, Fourier transforms, Sensors, Humidity

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The ultimate remote sensing benefits of the high resolution Infrared radiance spectrometers will be realized with their geostationary satellite implementation in the form of imaging spectrometers. This will enable dynamic features of the atmosphere's thermodynamic fields and pollutant and greenhouse gas constituents to be observed for revolutionary improvements in weather forecasts and more accurate air quality and climate predictions. As an important step toward realizing this application objective, the Geostationary Imaging Fourier Transform Spectrometer (GIFTS) Engineering Demonstration Unit (EDU) was successfully developed under the NASA New Millennium Program, 2000-2006. The GIFTS-EDU instrument employs three focal plane arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The raw GIFTS interferogram measurements are radiometrically and spectrally calibrated to produce radiance spectra, which are further processed to obtain atmospheric profiles via retrieval algorithms. The radiometric calibration is achieved using internal blackbody calibration references at ambient (260 K) and hot (286 K) temperatures. The absolute radiometric performance of the instrument is affected by several factors including the FPA off-axis effect, detector/readout electronics induced nonlinearity distortions, and fore-optics offsets. The GIFTS-EDU, being the very first imaging spectrometer to use ultra-high speed electronics to readout its large area format focal plane array detectors, operating at wavelengths as large as 15 microns, possessed non-linearity's not easily removable in the initial calibration process. In this paper, we introduce a refined calibration technique that utilizes Principle Component (PC) analysis to compensate for instrument distortions and artifacts remaining after the initial radiometric calibration process, thus, further enhance the absolute calibration accuracy. This method is applied to data collected during an atmospheric measurement experiment with the GIFTS, together with simultaneous observations by the accurately calibrated AERI (Atmospheric Emitted Radiance Interferometer), both simultaneously zenith viewing the sky through the same external scene mirror at ten-minute intervals throughout a cloudless day at Logan Utah on September 13, 2006. The PC vectors of the calibrated radiance spectra are defined from the AERI observations and regression matrices relating the initial GIFTS radiance PC scores to the AERI radiance PC scores are calculated using the least squares inverse method. A new set of accurately calibrated GIFTS radiances are produced using the first four PC scores in the regression model. Temperature and moisture profiles retrieved from the PC-calibrated GIFTS radiances are verified against radiosonde measurements collected throughout the GIFTS sky measurement period.

Proceedings Article | 24 October 2007 Paper

GIFTS SM EDU Level 1B algorithms

Jialin Tian, Michael Gazarik, Robert Reisse, David Johnson

Proceedings Volume 6748, 674811 (2007) https://doi.org/10.1117/12.737326

KEYWORDS: Calibration, Staring arrays, Sensors, Black bodies, Fourier transforms, Detection and tracking algorithms, Infrared imaging, Spectral calibration, Optical filters, Spectroscopy

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The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) Sensor Module (SM) Engineering Demonstration Unit (EDU) is a high resolution spectral imager designed to measure infrared (IR) radiances using a Fourier transform spectrometer (FTS). The GIFTS instrument employs three focal plane arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The raw interferogram measurements are radiometrically and spectrally calibrated to produce radiance spectra, which are further processed to obtain atmospheric profiles via retrieval algorithms. This paper describes the GIFTS SM EDU Level 1B algorithms involved in the calibration. The GIFTS Level 1B calibration procedures can be subdivided into four blocks. In the first block, the measured raw interferograms are first corrected for the detector nonlinearity distortion, followed by the complex filtering and decimation procedure. In the second block, a phase correction algorithm is applied to the filtered and decimated complex interferograms. The resulting imaginary part of the spectrum contains only the noise component of the uncorrected spectrum. Additional random noise reduction can be accomplished by applying a spectral smoothing routine to the phase-corrected spectrum. The phase correction and spectral smoothing operations are performed on a set of interferogram scans for both ambient and hot blackbody references. To continue with the calibration, we compute the spectral responsivity based on the previous results, from which, the calibrated ambient blackbody (ABB), hot blackbody (HBB), and scene spectra can be obtained. We now can estimate the noise equivalent spectral radiance (NESR) from the calibrated ABB and HBB spectra. The correction schemes that compensate for the fore-optics offsets and off-axis effects are also implemented. In the third block, we developed an efficient method of generating pixel performance assessments. In addition, a random pixel selection scheme is designed based on the pixel performance evaluation. Finally, in the fourth block, the single pixel algorithms are applied to the entire FPA.

Proceedings Article | 18 April 2006 Paper

Development of an extra-vehicular (EVA) infrared (IR) camera inspection system

Michael Gazarik, Dave Johnson, Ed Kist, Frank Novak, Charles Antill, David Haakenson, Patricia Howell, John Pandolf, Rusty Jenkins, Rusty Yates, Ryan Stephan, Doug Hawk, Michael Amoroso

Proceedings Volume 6205, 62051C (2006) https://doi.org/10.1117/12.669683

KEYWORDS: Cameras, Infrared cameras, Imaging systems, Inspection, Infrared imaging, Thermography, Electronic components, Manufacturing, Thermal modeling, Infrared radiation

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Proceedings Article | 28 March 2005 Paper

Infrared on-orbit RCC inspection system (IORIS)

Michael Gazarik, Charles Antill, David Johnson, Ryan Stephan, Kevin Vipavetz, John Pandolf, Edward Kist, Nina Tappan, William Winfree, John Teter, David Haakenson, David Hinds, Brian Backer, Heather Wickman, Michael Harris

Proceedings Volume 5782, (2005) https://doi.org/10.1117/12.603167

KEYWORDS: Cameras, Infrared cameras, Inspection, Infrared imaging, Imaging systems, Electronics, Staring arrays, Sensors, Thermography, Visible radiation

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Proceedings Article | 20 October 1999 Paper

NAST-I: results from revolutionary aircraft sounding spectrometer

William Smith, Allen Larar, Daniel Zhou, Christopher Sisko, Jun Li, Bormin Huang, H. Benjamin Howell, Henry Revercomb, Daniel Cousins, Michael Gazarik, D. Mooney, Stephen Mango

Proceedings Volume 3756, (1999) https://doi.org/10.1117/12.366362

KEYWORDS: Sensors, Infrared radiation, Spectroscopy, Atmospheric modeling, Satellites, Calibration, Atmospheric optics, Spectral resolution, Atmospheric sensing, Infrared spectroscopy

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Proceedings Article | 24 September 1999 Paper

Noise performance of the NPOESS Airborne Sounder Testbed Interferometer (NAST-I) sounder: flight and model results

Michael Kelly, Michael Gazarik, Richard Marino

Proceedings Volume 3750, (1999) https://doi.org/10.1117/12.363520

KEYWORDS: Interferometers, Sensors, Performance modeling, Data modeling, Mirrors, Instrument modeling, Modulation, Satellites, Signal to noise ratio, Fourier transforms

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Proceedings Article | 3 October 1998 Paper

NPOESS airborne sounder testbed interferometer (NAST-I) signal processing and initial flight test results

Michael Gazarik, Lawrence Candell, Edward Leonard, Steven Prutzer

Proceedings Volume 3439, (1998) https://doi.org/10.1117/12.325656

KEYWORDS: Interferometers, Optical filters, Calibration, Signal processing, Mirrors, Digital signal processing, Black bodies, Filtering (signal processing), Satellites, Data acquisition

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Proceedings Article | 19 December 1996 Paper

Condition monitoring of production lines using event-time observers

Michael Gazarik, Edward Kamen

Proceedings Volume 2911, (1996) https://doi.org/10.1117/12.262500

KEYWORDS: Systems modeling, Time metrology, Model-based design, Manufacturing, Statistical analysis, Matrices, Error analysis, Automotive electronic systems, Electronic circuits, Process control

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