High resolution calibrated near infrared (NIR) imagery of the Space Shuttle Orbiter was obtained during hypervelocity
atmospheric re-entry of the STS-119, STS-125, STS-128, STS-131, STS-132, STS-133, and STS-134 missions. This
data has provided information on the distribution of surface temperature and the state of the airflow over the windward
surface of the Orbiter during descent. The thermal imagery complemented data collected with onboard surface
thermocouple instrumentation. The spatially resolved global thermal measurements made during the Orbiter's
hypersonic re-entry will provide critical flight data for reducing the uncertainty associated with present day ground-to-flight
extrapolation techniques and current state-of-the-art empirical boundary-layer transition or turbulent heating
prediction methods. Laminar and turbulent flight data is critical for the validation of physics-based, semi-empirical
boundary-layer transition prediction methods as well as stimulating the validation of laminar numerical chemistry
models and the development of turbulence models supporting NASA's next-generation spacecraft. In this paper we
provide details of the NIR imaging system used on both air and land-based imaging assets. The paper will discuss
calibrations performed on the NIR imaging systems that permitted conversion of captured radiant intensity (counts) to
temperature values. Image processing techniques are presented to analyze the NIR data for vignetting distortion, best
resolution, and image sharpness.
Ground-based high-resolution, calibrated, near-infrared (NIR) imagery of the Space Shuttle STS-134 Endeavour during
reentry has been obtained as part of NASA's HYTHIRM (Hypersonic Thermodynamic InfraRed Measurements) project.
The long-range optical sensor package called MARS (Mobile Aerospace Reconnaissance System) was positioned in
advance to acquire and track part of the shuttle re-entry. Imagery was acquired during a few minutes, with the best
imagery being processed when the shuttle was at 133 kft at Mach 5.8. This paper describes the processing of the NIR
imagery, building upon earlier work from the airborne imagery collections of several prior shuttle missions. Our goal is
to calculate the temperature distribution of the shuttle's bottom surface as accurately as possible, considering both
random and systematic errors, while maintaining all physical features in the imagery, especially local intensity
variations. The processing areas described are: 1) radiometric calibration, 2) improvement of image quality, 3)
atmospheric compensation, and 4) conversion to temperature. The computed temperature image will be shown, as well
as comparisons with thermocouples at different positions on the shuttle. A discussion of the uncertainties of the
temperature estimates using the NIR imagery is also given.
Detection and characterization of space objects require the capability to derive physical properties such as brightness
temperature and reflectance. These quantities, together with trajectory and position, are often used to correlate an object
from a catalogue of known characteristics. However, retrieval of these physical quantities can be hampered by the
radiative obscuration of the atmosphere. Atmospheric compensation must therefore be applied to remove the radiative
signature of the atmosphere from electro-optical (EO) collections and enable object characterization.
The JHU/APL Atmospheric Compensation System (ACS) was designed to perform atmospheric compensation for long,
slant-range paths at wavelengths from the visible to infrared. Atmospheric compensation is critically important for airand
ground-based sensors collecting at low elevations near the Earth's limb. It can be demonstrated that undetected thin,
sub-visual cirrus clouds in the line of sight (LOS) can significantly alter retrieved target properties (temperature,
irradiance). The ACS algorithm employs non-traditional cirrus datasets and slant-range atmospheric profiles to estimate
and remove atmospheric radiative effects from EO/IR collections. Results are presented for a NASA-sponsored
collection in the near-IR (NIR) during hypersonic reentry of the Space Shuttle during STS-132.
High-resolution, calibrated, near-infrared imagery of the Space Shuttle during reentry has been obtained by a US Navy
NP-3D Orion aircraft as part of NASA's HYTHIRM (Hypersonic Thermodynamic InfraRed Measurements) project. The
long-range optical sensor package is called Cast Glance. Three sets of imagery have been processed thus far: 1) STS-
119 when Shuttle Discovery was at 52 km away at Mach 8.4, 2) STS-125 when Shuttle Atlantis was 71 km away at
Mach 14.3, and 3) STS-128 when Shuttle Discovery was at 80 km away at Mach 14.7. The challenges presented in
processing a manually-tracked high-angular rate, air-to-air image data collection include management of significant
frame-to-frame motions, motion-induced blurring, changing orientations and ranges, daylight conditions, and sky
backgrounds (including some cirrus clouds). This paper describes processing the imagery to estimate Shuttle surface
temperatures. Our goal is to reduce the detrimental effects due to motions (sensor and Shuttle), vibration, and
atmospherics for image quality improvement, without compromising the quantitative integrity of the data, especially
local intensity variations. Our approach is to select and utilize only the highest quality images, register many cotemporal
image frames to a single image frame, and then add the registered frames to improve image quality and reduce
noise. These registered and averaged intensity images are converted to temperatures on the Shuttle's windward surface
using a series of steps starting with preflight calibration data. Comparisons with thermocouples at different points along
the space Shuttle and between the three reentries will be shown.
Long-wave infrared hyperspectral sensors provide the ability to detect gas plumes at stand-off distances. A number of
detection algorithms have been developed for such applications, but in situations where the gas is released in a complex
background and is at air temperature, these detectors can generate a considerable amount of false alarms. To make
matters more difficult, the gas tends to have non-uniform concentrations throughout the plume making it spatially similar
to the false alarms. Simple post-processing using median filters can remove a number of the false alarms, but at the cost
of removing a significant amount of the gas plume as well. We approach the problem using an adaptive subpixel detector
and morphological processing techniques. The adaptive subpixel detection algorithm is able to detect the gas plume
against the complex background. We then use morphological processing techniques to isolate the gas plume while
simultaneously rejecting nearly all false alarms. Results will be demonstrated on a set of ground-based long-wave
infrared hyperspectral image sequences.
The FIRST, a commercial hyperspectral imager developed by Telops, features high sensitivity in a
compact and robust package. This sensor provides hypercubes of spectral radiance of up to 320x256
pixels at 0.35mrad spatial resolution over the 8 - 12 &mgr;m spectral range at user selectable spectral
resolutions of up to 0.25 cm<sup>-1</sup>. The measurements are converted into "chemical maps" by the use of
powerful algorithms using both spatial and spectral information. The FIRST has been used at several field
tests for the standoff detection and identification of chemicals. During these tests, the sensor is usually
operated at 4 cm<sup>-1</sup> of spectral resolution and the image size is tailored according to the dissemination.
Algorithms based on a combination of clutter-matched filters and spectral angle mapper have been
developed and used to process the measured data. The algorithms combine sub-band selection to
minimize the correlation between the spectral signatures in the library and careful selection of the
thresholds to reduce the level of false alarms. The output of the algorithms is the image of the clouds
superimposed on the broadband thermal image. JHU/APL has developed a processing approach that
adapts to different backgrounds, yields low probability of false alarm, and performs well in the presence
of "hot" pixels. The algorithm combines background/noise suppression techniques, spectral detection
techniques, such as the spectral angle mapper and the matched filter, and automatic adaptive threshold
techniques. This paper will present the successful standoff detection and identification of various
chemical compounds using a variety of field measurements. Images of chemical disseminations will be
presented, with some of them including mixtures of 2 different chemicals.
To more precisely measure and monitor bone health, The Johns Hopkins University Applied Physics Lab and School of Medicine have developed the Advanced Multiple Projection Dual-Energy X-Ray Absorptiometry (AMPDXA) scanner. This system provides improvements over conventional DXA scanners in image resolution and multiple projection capability. These improvements allow us to determine structural information about the bone in addition to the standard bone mineral density (BMD) measurements. Algorithms and software were developed to process data acquired from the AMPDXA scanner and to determine important structural parameters, such as the center of mass axis in three dimensions and cross-sectional moments of inertia. The analysis operates on three projections about 15 degrees apart, calculates BMD for each projection, and then combines the data into a three dimensional coordinate system. By knowing the patient position in three dimensions, bone structural parameters are calculated more precisely. Using repeated testing of cadaver bones, the precision of determining these structural parameters is approximately the detector pixel size of 0.127 mm. Data on artificial bone cylinders indicate accuracy of about 3%. Comparisons between bone structural parameters derived from AMPDXA and CT scans show very similar results.
The CONTOUR Remote Imager and Spectrometer (CRISP) was a multi-function optical instrument developed for the Comet Nucleus Tour Spacecraft (CONTOUR). CONTOUR was a NASA Discovery class mission launched on July 3, 2002. This paper describes the design, fabrication, and testing of CRISP. Unfortunately, the CONTOUR spacecraft was destroyed on August 15, 2002 during the firing of the solid rocket motor that injected it into heliocentric orbit. CRISP was designed to return high quality science data from the solid nucleus at the heart of a comet. To do this during close range (order 100 km) and high speed (order 30 km/sec) flybys, it had an autonomous nucleus acquisition and tracking system which included a one axis tracking mirror mechanism and the ability to control the rotation of the spacecraft through a closed loop interface to the guidance and control system. The track loop was closed using the same images obtained for scientific investigations. A filter imaging system was designed to obtain multispectral and broadband images at resolutions as good as 4 meters per pixel. A near IR imaging
spectrometer (or hyperspectral imager) was designed to obtain spectral signatures out to 2.5 micrometers with resolution of better than 100 meters spatially. Because of the high flyby speeds, CRISP was designed as a highly automated instrument with close coupling to the spacecraft, and was intended to obtain its best data in a very short period around closest approach. CRISP was accompanied in the CONTOUR science payload by CFI, the CONTOUR Forward Imager. CFI was optimized for highly sensitive observations at greater ranges. The two instruments provided highly complementary optical capabilities, while providing some degree of functional redundancy.