F. De Luccia

High‐detectivity GaAs quantum well infrared detectors with peak responsivity at 8.2 μm

GaAs quantum well infrared detectors with peak responsivity at 8.2 μm and significant response beyond 10 μm have been demonstrated with detectivities of 4×1011 cm (Hz)1/2 /W at 6 K; this detectivity is the highest reported for a quantum well detector. The detectors comprised 50 GaAs quantum wells of width 40 A with an average Si doping density of 1×1018 cm−3 separated by 280‐A barriers of Al0.28Ga0.72As. In this design, the state to which electrons are excited by infrared absorption and from which they are subsequently collected lies in the continuum above the energy of the Al0.28Ga0.72As conduction‐band minimum. The maximum detector responsivity was mesured to be 0.34 A/W. The device dark current density is 5.5×10−6 A/cm2 with the detector biased for maximum detectivity (3.5 V), and the dark current remains constant with increasing temperature up to 50 K. The detector noise current was observed to be a constant fraction (70%) of the shot noise down to noise currents of 10−14 A/(Hz)1/2. A theoretical mode...

VIIRS thermal emissive bands calibration algorithm and on-orbit performance

The Visible-Infrared Imaging Radiometer Suite (VIIRS) was launched October 28, 2011 on-board the Suomi National Polar-orbiting Partnership (NPP) spacecraft as a primary sensor. It has 22 bands: 14 reflective solar bands (RSBs), 7 thermal emissive bands (TEBs) and a Day Night Band (DNB). There are 2 TEBs with a resolution of 371 m and 5 with 742 m which cover the spectral wavelengths between 3.7 to 12 μm. In addition to sea surface temperature (SST), a VIIRS Key Performance Parameter (KPP), the TEB detector dynamic range and spectral placement allow cloud, atmospheric and surface temperatures as well as water vapor to be measured. VIIRS TEB on-orbit calibration uses a quadratic algorithm with its calibration coefficients derived from pre-launch measurements and an on-board calibration blackbody (OBC BB) to provide scan-to-scan gain drift compensation. This paper will discuss the calibration methodology, OBC BB performance and stability, detector noise equivalent delta temperature and radiometric performance.

VIIRS solar diffuser bidirectional reflectance distribution function (BRDF) degradation factor operational trending and update

The Visible-Infrared Imaging Radiometer Suite (VIIRS) was launched onboard the Suomi National Polar-orbiting Partnership (NPP) spacecraft on October 28, 2011. Among the bands on VIIRS are 14 reflective solar bands (RSBs). The RSBs are calibrated using the sun as a source, after attenuation and reflection of sunlight from a Solar Diffuser (SD). The reflectance of the SD is known to degrade over time, particularly at the blue end of the visible spectrum. VIIRS incorporates a separate instrument, a Solar Diffuser Stability Monitor (SDSM), in order to measure and trend the SD Bidirectional Reflectance Distribution Function BRDF changes over time. Inadequate knowledge of the SDSM screen transmission as a function of solar geometry and SDSM detector dependent modulation effects require a unique processing methodology to eliminate unphysical artifacts from the SD BRDF trending. The unique methodology is used to generate periodic updates to operational Look-up Tables (LUTs) used by the Sensor Data Record (SDR) operational code to maintain the calibration of the RSBs. This paper will discuss on-orbit SD BRDF behavior along with the processing methodology used to generate RSB LUT updates incorporating the trended SD BRDF behavior.

Discovery and characterization of on-orbit degradation of the VisibleInfrared Imaging Radiometer Suite (VIIRS) Rotating TelescopeAssembly (RTA)

The Suomi National Polar-orbiting Partnership (NPP) satellite was launched on Oct. 28, 2011, and began the commissioning phase of several of its instruments shortly thereafter. One of these instruments, VIIRS, was found to exhibit a gradual but persistent decrease in the optical throughput of several bands, with the near-infrared bands being more affected than those in the visible. The rate of degradation quickly increased upon opening of the nadir door that permits the VIIRS telescope to view the earth. Simultaneously, a second instrument on NPP, the Solar Diffuser Stability Monitor (SDSM), was experiencing a similar decrease in response, leading the investigation team to suspect that the cause must be the result of some common contamination process. This paper will discuss a series of experiments that were performed to demonstrate that the VIIRS and SDSM response changes were due to separate causes, and which enabled the team to conclude that the VIIRS sensor degradation was the result of ultraviolet light exposure of the rotating telescope assembly. The root cause investigation of the telescope degradation will be addressed in a separate paper.

VIIRS day-night band gain and offset determination andperformance

On October 28th, 2011, the Visible-Infrared Imaging Radiometer Suite (VIIRS) was launched on-board the Suomi National Polar-orbiting Partnership (NPP) spacecraft. The instrument has 22 spectral bands: 14 reflective solar bands (RSB), 7 thermal emissive bands (TEB), and a Day Night Band (DNB). The DNB is a panchromatic, solar reflective band that provides visible through near infrared (IR) imagery of earth scenes with radiances spanning 7 orders of magnitude. In order to function over this large dynamic range, the DNB employs a focal plane array (FPA) consisting of three gain stages: the low gain stage (LGS), the medium gain stage (MGS), and the high gain stage (HGS). The final product generated from a DNB raw data record (RDR) is a radiance sensor data record (SDR). Generation of the SDR requires accurate knowledge of the dark offsets and gain coefficients for each DNB stage. These are measured on-orbit and stored in lookup tables (LUT) that are used during ground processing. This paper will discuss the details of the offset and gain measurement, data analysis methodologies, the operational LUT update process, and results to date including a first look at trending of these parameters over the early life of the instrument.

Comparison of VIIRS pre-launch RVS performance using results from independent studies

The Visible Infrared Imaging Radiometer Suite (VIIRS) is a key sensor carried on the NPOESS (National Polar-orbiting Operational Environmental Satellite System) Preparatory Project (NPP) mission [1] (http://jointmission.gsfc.nasa.gov/viirs.html), and is scheduled to launch in October 2011. VIIRS sensor design draws on heritage instruments including AVHRR, OLS, MODIS, and SeaWiFS. It has on-board calibration components including a solar diffuser (SD) and a solar diffuser stability monitor (SDSM) for the reflective solar bands (RSB), a V-groove blackbody for the thermal emissive bands (TEB), and a space view (SV) port for background subtraction. These on-board calibrators are located at fixed scan angles. The VIIRS response versus scan angle (RVS) was characterized prelaunch in lab ambient conditions and will be used on-orbit to characterize the response for all scan angles relative to the calibrator scan angle (SD for RSB and blackbody for TEB). Since the RVS is vitally important to the quality of calibrated radiance products, several independent studies were performed and their results were compared and validated. This document provides RVS results from three groups: the NPP Instrument Calibration Support Team (NICST), Raytheon, and the Aerospace Corporation. A comparison of the RVS results obtained using a 2nd order polynomial fit to measurement data is conducted for each band, detector, and half angle mirror (HAM) side. The associated RVS fitting residuals are examined and compared with the relative differences in RVS found between independent studies. Results show that the agreement is within 0.1% and comparable with fitting residuals for all bands except for RSB band M9, where a difference of 0.2% was observed. Band M9 is highly sensitive to the atmospheric water vapor variations during the sensor ambient testing at Raytheon, and its correction might be a contributor to the observed RVS uncertainty differences. In general, NICST results have shown slightly larger RSB RVS uncertainties but still well within the 0.3% total uncertainty allowed for the RVS characterization defined in the Performance Verification Plan.

VIIRS reflective solar bands on-orbit calibration coefficient performance using imagery and moderate band intercomparisons

A primary sensor on-board the Suomi-National Polar-orbiting Partnership (SNPP) spacecraft, the Visible Infrared Imaging Radiometer Suite (VIIRS) has 22 bands: 7 thermal emissive bands (TEBs), 14 reflective solar bands (RSBs) and a Day Night Band (DNB). The RSBs cover the spectral wavelengths between 0.412 to 2.25 μm and have three (I1-I3) 371m and eleven (M1-M11) 742m spatial resolution bands. A VIIRS Key Performance Parameter (KPP) is the Ocean Color/Chlorophyll (OCC) which uses moderate bands M1 (0.412μm) through M7’s (0.865 μm) calibrated Science Data Records (SDRs). The RSB SDRs rely on prelaunch calibration coefficients which use a quadratic algorithm to convert the detector’s response to calibrated radiance. This paper will evaluate the performance of these prelaunch calibration coefficients using SDR comparisons between bands with the same spectral characteristics: I2 with M7 (0.865 μm) and I3 with M10 (1.610 μm). Changes to the prelaunch calibration coefficient’s offset term c0 to improve the SDR’s performance at low radiance levels will also be discussed.

VIIRS thermal emissive bands on-orbit calibration coefficient performance using vicarious calibration results

The Visible Infrared Imager Radiometer Suite (VIIRS), a primary sensor on-board the Suomi-National Polar-orbiting Partnership (SNPP) spacecraft, was launched October 28, 2011. It has 22 bands: 7 thermal emissive bands (TEBs), 14 reflective solar bands (RSBs) and a Day Night Band (DNB). The TEBs cover the spectral wavelengths between 3.7 to 12 μm and have two 371 m and five 742 m spatial resolution bands. A VIIRS Key Performance Parameter (KPP) is the sea surface temperature (SST) which uses bands M12 (3.7 μm), M15 (10.8 μm) and M16’s (12.0 μm) calibrated Science Data Records (SDRs). The TEB SDRs rely on pre-launch calibration coefficients used in a quadratic algorithm to convert the detector’s response to calibrated radiance. This paper will evaluate the performance of these prelaunch calibration coefficients using vicarious calibration information from the Cross-track Infrared Sounder (CrIS) also onboard the SNPP spacecraft and the Infrared Atmospheric Sounding Interferometer (IASI) on-board the Meteorological Operational (MetOp) satellite. Changes to the pre-launch calibration coefficients’ offset term c0 to improve the SDR’s performance at cold scene temperatures will also be discussed.

Mission history of reflective solar band calibration performance of VIIRS

Environmental Data Records (EDR) from the Visible Infrared Imaging Radiometer Suite (VIIRS) have a need for Reflective Solar Band (RSB) calibration errors of less than 0.1%. Throughout the mission history of VIIRS, the overall instrument calibrated response scale factor (F factor) has been calculated with a manual process that uses data at least one week old and up to two weeks old until a new calibration Look Up Table (LUT) is put into operation. This one to two week lag routinely adds more than 0.1% calibration error. In this paper, we discuss trending the solar diffuser degradation (H factor), a key component of the F factor, improving H factor accuracy with improved bidirectional reflectance distribution function (BRDF) and attenuation screen LUTs , trending F factor, and how using RSB Automated Calibration (RSBAutoCal) will eliminate the lag and look-ahead extrapolation error.

Reply to ‘‘Comment on ‘High‐detectivity GaAs quantum‐well infrared detectors with peak responsivity at 8.2 μm’ ’’

The expression for the ratio between the noise current and full shot noise contained in our recent paper [J. Appl. Phys. 67, 7608 (1990)] is based entirely on standard generation‐recombination noise theory, and does not represent a more complex model as Beck suggests [J. Appl. Phys. 69, xxx (1991)]. The equations presented by Beck contain errors, but once these errors are corrected, his equations and ours yield the same quantitative predictions.