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This PDF file contains the front matter associated with SPIE
Proceedings Volume 7087, including the Title Page, Copyright
information, Table of Contents, Introduction (if any), and the
Conference Committee listing.
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The design of any modern imaging system is the end result of many trade studies, each seeking to optimize image
quality within real world constraints such as cost, schedule and overall risk. Image chain analysis - the prediction of
image quality from fundamental design parameters - is an important part of this design process. At The Aerospace
Corporation we have been using a variety of image chain analysis tools for many years, the Parameterized Image Chain
Analysis & Simulation SOftware (PICASSO) among them. In this paper we describe our PICASSO tool, showing how,
starting with a high quality input image and hypothetical design descriptions representative of the current state of the art
in commercial imaging satellites, PICASSO can generate standard metrics of image quality in support of the decision
processes of designers and program managers alike.
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In this paper we model sub-pixel image registration for a generic earth-observing satellite system with a focal plane
using two offset Time Delay and Integrate (TDI) arrays in the focal plane to improve the achievable ground resolution
over the resolution achievable with a single array. The modeling process starts with a high-resolution image as ground
truth. The Parameterized Image Chain Analysis & Simulation SOftware (PICASSO) modeling tool is used to degrade
the images to match the optical transfer function, sampling, and noise characteristics of the target system. The model
outputs a pair of images with a separation close to the nominal half-pixel separation between the overlapped arrays. A
registration estimation algorithm is used to measure the offset for image reconstruction. The two images are aligned and
summed on a grid with twice the capture resolution. We compare the resolution in images between the inputs before
overlap, the reconstructed image, and a simulation for the image which would have been captured on a focal plane with
twice the resolution. We find the performance to always be better than the lower resolution baseline, and to approach
the performance of the high-resolution array in the ideal case. We show that the overlapped array imager significantly
outperforms both the conventional high- and low-resolution imagers in conditions with high image smear.
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In system performance analysis, most often Signal to Noise Ratio (SNR) and system resolution (via
MTF) are analyzed separately. In this paper we advocate the use of a joint measure, namely, the Noise
Equivalent Reflectance Difference (NERD) as a function of the Spatial Resolution (SR). We
demonstrate that the NERD vs. SR captures most of the essential properties of the system's
performances and is therefore a useful tool in system evaluation. We demonstrate how various
tradeoffs affect the NERD vs. SR curve in some not so trivial way.
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The Centro Nazionale di Meteorologia e Climatologia Aeronautica recently hosted a fellowship sponsored by Galileo
Avionica, with the intent to study and perform a simulation of Meteosat Third Generation - Lightning Imager (MTG-LI)
sensor behavior through Tropical Rainfall Measuring Mission - Lightning Imaging Sensor data (TRMM-LIS). For the
next generation of earth observation geostationary satellite, major operating agencies are planning to insert an optical
imaging mission, that continuously observes lightning pulses in the atmosphere; EUMETSAT has decided in recent
years that one of the three candidate mission to be flown on MTG is LI, a Lightning Imager. MTG-LI mission has no
Meteosat Second Generation heritage, but users need to evaluate the possible real time data output of the instrument to
agree in inserting it on MTG payload. Authors took the expected LI design from MTG Mission Requirement Document,
and reprocess real lightning dataset, acquired from space by TRMM-LIS instrument, to produce a simulated MTG-LI
lightning dataset. The simulation is performed in several run, varying Minimum Detectable Energy, taking into account
processing steps from event detection to final lightning information. A definition of the specific meteorological
requirements is given from the potential use in meteorology of lightning final information for convection estimation and
numerical cloud modeling. Study results show the range of instrument requirements relaxation which lead to minimal
reduction in the final lightning information.
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Observing System Simulation Experiments (OSSEs) are an important tool for evaluating the potential impact of
proposed new observing systems, as well as for evaluating trade-offs in observing system design, and in developing and
assessing improved methodology for assimilating new observations. Extensive OSSEs have been conducted at NASA/
GSFC and NOAA/AOML in collaboration with Simpson Weather Associates and operational data assimilation centers
over the last 23 years. These OSSEs determined correctly the quantitative potential for several proposed satellite
observing systems to improve weather analysis and prediction prior to their launch, evaluated trade-offs in orbits,
coverage and accuracy for space-based wind lidars, and were used in the development of the methodology that led to the
first beneficial impacts of satellite surface winds on numerical weather prediction. In this paper, we summarize OSSE
methodology and earlier OSSE results, and present methodology and results from recent OSSEs.
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This paper focuses on the fundamental system engineering tradeoff driving almost all remote sensing design efforts, affecting complexity, cost, performance, schedule, and risk: image quality vs. sensitivity. This single trade encompasses every aspect of performance, including radiometric accuracy, dynamic range and precision, as well as spatial, spectral, and temporal coverage and resolution. This single trade also encompasses every aspect of design, including mass, dimensions, power, orbit selection, spacecraft interface, sensor and spacecraft functional trades, pointing or scanning architecture, sensor architecture (e.g., field-of-view, optical form, aperture, f/#, material properties), electronics, mechanical and thermal properties. The relationship between image quality and sensitivity is introduced based on the concepts of modulation transfer function (MTF) and signal-to-noise ratio (SNR) with examples to illustrate the balance to be achieved by the system architect to optimize cost, complexity, performance and risk relative to end-user requirements.
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In modern horror fiction, zombies are generally undead corpses brought back from the dead by supernatural or
scientific means, and are rarely under anyone's direct control. They typically have very limited intelligence, and
hunger for the flesh of the living [1].
Typical spectroradiometric or hyperspectral instruments
providess calibrated radiances for a number of remote
sensing algorithms. The algorithms typically must meet
specified latency and availability requirements while
yielding products at the required quality. These systems,
whether research, operational, or a hybrid, are typically
cost constrained. Complexity of the algorithms can be
high, and may evolve and mature over time as sensor
characterization changes, product validation occurs, and
areas of scientific basis improvement are identified and
completed. This suggests the need for a systems
engineering process for algorithm maintenance that is
agile, cost efficient, repeatable, and predictable.
Experience on remote sensing science data systems
suggests the benefits of "plug-n-play" concepts of
operation. The concept, while intuitively simple, can be
challenging to implement in practice. The use of zombie
algorithms-empty shells that outwardly resemble the
form, fit, and function of a "complete" algorithm without
the implemented theoretical basis-provides the ground
systems advantages equivalent to those obtained by
integrating sensor engineering models onto the spacecraft
bus. Combined with a mature, repeatable process for
incorporating the theoretical basis, or scientific core, into
the "head" of the zombie algorithm, along with
associated scripting and registration, provides an easy
"on ramp" for the rapid and low-risk integration of
scientific applications into operational systems.
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A new set of cross-calibrated, multi-satellite ocean surface wind data is described. The principal data set covers the
global ocean for the period beginning in 1987 with six-hour and 25-km resolution, and is produced by combining all
ocean surface wind speed observations from SSM/I, AMSR-E, and TMI, and all ocean surface wind vector observations
from QuikSCAT and SeaWinds. An enhanced variational analysis method (VAM) performs quality control and
combines these data with available conventional ship and buoy data and ECMWF analyses. The VAM analyses fit the
data used very closely and contain small-scale structures not present in operational analyses. Comparisons with withheld
WindSat observations are also shown to be very good. These data sets should be extremely useful to atmospheric and
oceanic research, and to air-sea interaction studies.
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Earth observation satellites employ various types of remote-sensing instruments to peer into the secrets of the
atmosphere. Many of these instruments collect two-dimensional data stored as raster images which can be easily georeferenced
and overlaid onto a virtual globe, with stunning results. However, certain instruments collect threedimensional
science data which can pose a significant challenge for visualization efforts. The Tropospheric Emission
Spectrometer (TES) is such an instrument which collects scientific data about atmospheric chemistry and stores the
outputs in an Oracle database. With some imaginative programming, the data is transformed into interesting and
information-packed visualizations using shell scripts, SQL scripts and Oracle stored procedures to yield Google Earthformatted
files. This Google Earth content is hosted on the TES external web site for use by the public.
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Raytheon recently developed and implemented a Near Real Time (NRT) data processing subsystem for Earth Observing
System (EOS) Microwave Limb Sounder (MLS3) instrument on NASA Aura spacecraft. The NRT can be viewed as a
customized Science Information Processing System (SIPS) where the measurements and information provided by the
instrument are expeditiously processed, packaged, and delivered. The purpose of the MLS NRT is to process Level 0
data up through Level 2, and distribute standard data products to the customer within 3-5 hours of the first set of data
arrival.
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Future operational geosynchronous remote sensors will respond to a broad range of environmental and
military/intelligence mission needs. This paper describes initial system engineering design studies for 4th
generation operational geosynchronous remote sensors that address notional future mission requirements.
Two hyperspectral sensor architectures were considered: an imaging Fourier transform spectrometer and an
imaging prism spectrometer. While both imaging FTS and dispersive approaches are viable over a broad
trade space, each requires new technology that must be demonstrated low risk by 2017 to enable a mission
pathfinder by 2025. To reach this important objective requires that technology risk reduction start now.
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Closed-cycle mechanical cryogenic refrigerators, or cryocoolers, are an enabling technology for next generation
infrared (IR) sensors. Passive cryoradiators and stored cryogen systems have been used successfully in the past, but the
increased cooling requirements for emerging systems cannot practically be met with these passive techniques. Modern
systems are employing much larger focal plane arrays that dissipate more energy and have higher parasitic thermal loads
than in the past. Additional "on chip" FPA data processing capability, such as time delay and integration (TDI) and
analog-to-digital conversion (ADC), is further driving up the heat loads. While loads are going up, temperatures are
going down. The desire to operate at long wave infrared (LWIR) wavelengths (>9 microns) for a broader range of
remote sensing missions is driving the need for 35-40 K refrigeration, significantly colder than past systems that operated
at shorter wavelengths. Unfortunately, the use of a mechanical rather than passive cryocooler introduces an additional
jitter source that must be properly mitigated. Techniques include the use of inherently low vibration cryocoolers, closedloop
active vibration cancellation servo systems, damping struts, soft mounts, or a combination of these techniques.
Implementation of these techniques within a proper system engineering context is presented.
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A novel fiber optic sensor has been developed to be used in superconducting magnets for fusion reactors and other large
cable-in-conduit superconductor (CICC) magnet applications. These large superconducting magnets need a diagnostic
that can measure the temperature and strain throughout the magnet in real-time, which was not possible until now.
Simultaneous temperature and strain measurements at cryogenic temperatures have been demonstrated, using
spontaneous Brillouin scattering in an optical fiber. Using an extremely narrow (100 Hz) linewidth Brillouin laser with
very low noise as a frequency shifted local oscillator, the frequency shift of spontaneous Brillouin scattered light was
measured using heterodyne detection. A pulsed laser was used to probe the fiber using Optical Time Domain
Reflectometry (OTDR) to determine spatial resolution. The spontaneous Brillouin frequency shift and linewidth as a
function of temperature agree with previous literature on stimulated Brillouin scattering data from room temperature
down to 4 K. For the first time, the spontaneous Brillouin frequency shift, linewidth, and intensity as a function of strain
have been measured down to 4 K. Analyzing the frequency spectrum of the scattered light after an FFT gives the
Brillouin frequency shift, linewidth, and intensity of the scattered light. 65,000 pulses, with 53 ns pulse widths, were
averaged in under one second, providing a 5 meter spatial resolution along a fiber that was about 100 m long. Measuring
these three parameters allow the simultaneous determination of temperature and strain in real-time throughout a fiber
with a spatial resolution on the order of several meters.
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Spatial and temporal data derived from eye movements, compiled while the human eye observes geospatial
imagery, retain meaningful and usable information. When human perceives the stereo effect, the virtual three
dimensional (3D) model resulting from eye-brain interaction is generated in the mind. If the eye movements are
recorded while the virtual model is observed, it is possible to reconstruct a 3D geometrical model almost identical
to the one generated in the human brain. Information obtained from eye-movements can be utilized in many
ways for remote sensing applications such as geospatial image analysis and interpretation. There are various eyetracking
systems available on the market; however, none of them is designed to work with stereoscopic imagery.
We explore different approaches and designs of the most suitable and non-intrusive scheme for stereoscopic image
viewing in the eye-tracking systems to observe and analyze 3D visual models. The design of the proposed system
is based on the optical separation method, which provides visually comfortable environment for perception of
stereoscopic imagery. A proof of concept solution is based on multiple mirror-lens assembly that provides a
significant reduction of geometrical constrains in eye-frame capturing. Two projected solutions: for wide-angle
of viewing and helmet-integrated eye-tracker are also discussed here.
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The possibilities of the development of the 1-D tomographic fiber-optical measuring system based upon the set of the
loop-shaped fiber-optical measuring lines with different lengths were investigated. Single fiber multimode
interferometers were proposed as measuring lines. The system's signals processing algorithm was developed. The
scheme of the arrangement of the single fiber multimode interferometers in the 1-D multichannel tomographic system
was offered. The reconstruction of the lateral deformation pattern in the object (structural beam) under study was shown.
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Commercial Assets in Future Remote Sensing Systems
A unique opportunity exists to host up to 66 earth observation sensors on the Iridium NEXT LEO constellation in a
manner that can revolutionize earth observation and weather predictions. A constellation approach to sensing, using
the real-time communications backbone of Iridium, will enable unprecedented geospatial and temporal sampling for
now-casting of weather on a global basis as well as global climate monitoring. The Iridium NEXT constellation, with
66 interconnected satellites in 6 near polar orbiting planes, provides a unique platform for hosting a variety of earth
observation missions.
The opportunity is proposed as a Public-Private Partnership (PPP) allowing for the sharing of infrastructure by
government agencies. This has the potential to augment current and planned climate and weather observation
programs in a very cost effective manner not achievable in any other way. Iridium, with the assistance of the Group on
Earth Observations (GEO), NASA, NOAA, and ESA, has evaluated a number of sensing missions that would be a
good fit to the Iridium NEXT constellation. These include GPS radio occultation sensors, earth radiation budget
measurements, radio altimetry, tropospheric and stratospheric winds measurements including polar winds
measurements, and atmospheric chemistry. Iridium NEXT launches start in 2013 and constellation operational life will
extend beyond 2030. Detailed feasibility studies on specific missions are planned to begin later this year.
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The Global War on Terror, program overruns, and increasing demand for new capabilities has placed an ever increasing strain on National Space Assets, from communications satellites to earth and space observing systems. This strain has also created an opportunity. With the goal of increasing the number and capability of space-based payloads-at reduced costs compared to dedicated systems-the concept of "Hosted Payloads" [1] has recently been attracting the attention of both Government and Industry as an example of how the government can do things differently and focus on capabilities, not systems. The Hosted Payload concept infers that a commercial satellite is used as a platform on which a secondary payload gains access to space by sharing the costs of the bus, the launch, and the insurance. This paper describes the Hosted Payload vision and strategy, and the specific requirements for access to space. It describes the commercial best practices and technical systems trade offs in size, weight and power (SWaP) for deploying a hosted payload onboard an Intelsat satellite.
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The Iridium communications satellite constellation is a swarm of 66 LEO satellites in 6 pole-crossing orbits. Iridium
LLC plans a NEXT generation to be launched 2013-16, and has invited secondary "bolt and go" payloads from Earthobserving
agencies. A swarm of infrared imagers on Iridium-NEXT could track water vapor and clouds to estimate the
unobserved winds above the 55-60 degree latitude limit of geosynchronous satellite imagery. This kind of polar overpass
data has been demonstrated to significantly improve medium-range weather forecasts by tracking water vapor features at
6.7 microns in successive images near the pole from NASA's MODIS instruments. A "Boreas" instrument design is
proposed for a push-broom imager combining two miniature sensors: uncooled microbolometric cameras gathering 4-
band infrared radiometry, and small star trackers providing attitude information. An autonomous instrument package
has been designed with low mass, power, and data rate. The "Boreas" instrument would use the Iridium constellation
itself to relay the raw imagery from 3 successive images to ground stations that would navigate the data and extract wind
vectors. Wind vectors could be generated automatically for the polar caps every few hours, and delivered for
assimilation into numerical weather models during Iridium-NEXT operations, during 2016-2030.
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Existing Ocean Color sensors are near or beyond the end of their mission lives and there will likely be a gap in climate
quality Environmental Data Records (EDRs) until planned missions are launched. GeoEye's OrbView2 satellite with the
SeaWiFS sensor has provided a 10+ year climatology of global chlorophyll and other EDRs important for climate
change and global warming studies. Upcoming sensors will not provide sufficient accuracy to provide continuity for the
EDR time series and global monitoring. A 'stop-gap' mission is required and we propose using the existing spare
SeaWIFS sensor and a launch share with the future GeoEye-2 satellite.
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A standardized interface has been developed for the integration and accommodation of secondary payloads on to Orbital
Sciences Corporation's StarBus line of GEO-based commercial communications satellites. This standardized interface
through hardware adaptations and methodology incorporates all the major subsystems of the spacecraft and will allow
for a variety of hosted secondary payloads to be accommodated while not interfering with the "spacecraft product line"
manufacturing scheme common on commercial communications satellites. Indeed the low cost and fast schedules,
typically two years from contract start to launch, for commercial communications satellites relies upon a high level of
design standardization and exacting heritage. The Hosted Payloads interface as developed and exercised on the StarBus
makes the hosted payload components look like the usual communications components that are routinely comprise the
standard bent-pipe type of communications payload architecture - the kind of payload that the host spacecraft is
optimized to carry. Furthermore the hosted payload accommodation methodology has been developed to flow into the
timeline of the host spacecraft while still allowing for a small degree of margin. Being able to reconcile the aggressive
development process of a commercial communications satellites with the more elongated process seen in a remote
sensing payload is one necessary step to secure a viable future of commercially hosted payloads.
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