This PDF file contains the front matter associated with SPIE Proceedings Volume 7458, including the Title Page, Copyright information, Table of Contents, Introduction (if any), and the Conference Committee listing.

The Geostationary Operational Environmental Satellite R-series (GOES-R) is the follow-on to the existing GOES system, completing a transition from 1980's technology to state-of-the-art. The product of a collaborative development effort between NOAA, NASA, DOC and industry, the first GOES-R satellite is planned to be launched in April 2015 with readiness to fully replace the heritage GOES constellation in 2017. This next-generation system will continue as the United States' weather sentinel for forecasting hurricanes, severe storms, and flash floods while providing information about air quality, winds, sea surface temperature, and space weather. It will provide advanced capabilities by providing five times more spectral information, temporal coverage six times faster than the current system, and 50% higher spatial resolution. The heart of the GOES-R system is the ABI instrument, a sixteen-channel imager with six visible channels and 10 infrared channels. The GLM instrument will be the first geostationary sensor to detect and monitor lightning strikes. GOES-R also includes several space environment sensors that will increase the capability to monitor and predict solar flare activity. Additionally, GOES-R will continue to provide heritage search and rescue capabilities, a data collection system, and other direct readout capabilities.

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 11+ year climatology of global chlorophyll a 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 dedicated mission.

A 256x512 element digital image sensor has been developed which has a large pixel size, slow scan and low power consumption for Hyper Spectral Imager (HySI) applications. The device is a mixed mode, silicon on chip (SOC) IC. It combines analog circuitry, digital circuitry and optical sensor circuitry into a single chip. This chip integrates a 256x512 active pixel sensor array, a programming gain amplifier (PGA) for row wise gain setting, I²C interface, SRAM, 12 bit analog to digital convertor (ADC), voltage regulator, low voltage differential signal (LVDS) and timing generator. The device can be used for 256 pixels of spatial resolution and 512 bands of spectral resolution ranged from 400 nm to 950 nm in wavelength. In row wise gain readout mode, one can set a different gain on each row of the photo detector by storing the gain setting data on the SRAM thru the I²C interface. This unique row wise gain setting can be used to compensate the silicon spectral response non-uniformity problem. Due to this unique function, the device is suitable for hyper-spectral imager applications. The HySI camera located on-board the Chandrayaan-1 satellite, was successfully launched to the moon on Oct. 22, 2008. The device is currently mapping the moon and sending back excellent images of the moon surface. The device design and the moon image data will be presented in the paper.

The Compact InfraRed Camera (CIRC) is a technology-demonstration payload to be carried on the Small Demonstration Satellite type-2 (SDS-2). The SDS program is a JAXA activity to demonstrate a variety of new technologies and new missions. The CIRC is an infrared camera equipped with an uncooled infrared array detector (microbolometer). The mission of the SDS-2/CIRC project is to demonstrate the potential of the microbolometer, especially for wildfire detection but also for other applications. This paper introduces the detailed design and concept of CIRC. We also discuss preliminary results of the feasibility study on wildfire detection using thermal infrared images.

This paper focuses on system engineering development issues driving satellite remote sensing instrumentation cost and schedule. A key best practice is early assessment of mission and instrumentation requirements priorities driving performance trades among major instrumentation measurements: Radiometry, spatial field of view and image quality, and spectral performance. Key lessons include attention to technology availability and applicability to prioritized requirements, care in applying heritage, approaching fixed-price and cost-plus contracts with appropriate attention to risk, and assessing design options with attention to customer preference as well as design performance, and development cost and schedule. A key element of success either in contract competition or execution is team experience. Perhaps the most crucial aspect of success, however, is thorough requirements analysis and flowdown to specifications driving design performance with sufficient parameter margin to allow for mistakes or oversights - the province of system engineering from design inception to development, test and delivery.

Forward looking infrared and Radar (X-band or Ku-band) sensors are potential components in external hazard monitoring systems for general aviation aircraft. We are investigating the capability of these sensors to provide hazard information to the pilot when normal visibility is reduced by meteorological conditions. Fusing detection results from FLIR and Radar sensors can improve hazard detection performance. We have developed a demonstration fusion system for the detection of runway incursions. In this paper, we present our fusion system, along with detection results from data recorded on approach to a landing during clear daylight, overcast daylight, and clear night conditions.

Realistic simulated satellite imagery for GOES-R ABI using state of the art mesoscale modeling and accurate radiative transfer is being produced at the Cooperative Institute for Research in the Atmosphere (CIRA) and used in developing and testing new products. Products which have been produced in support of the GOES-R Algorithm Working Group (AWG) include 6-hour imagery at 5 minute intervals for 4 GOES-R ABI bands (2.25 μm, 3.9 μm, 10.35 μm, and 11.2 μm) that include fire hotspots. The imagery was initially produced at 400 m resolution and a point-spread function applied on the data to create ABI resolution imagery. Also created was corresponding imagery for current GOES at 2 bands (3.9 μm and 10.7 μm). These fire hotspots were simulated for 4 different cases over Kansas, Central America, and California. Additionally, high quality imagery for 10 GOES-R ABI bands (3.9 μm and higher) were produced for 4 extreme weather events. These simulations include a lake effect snow case, a severe weather case, Hurricane Wilma, and Hurricane Lili. All simulations for extreme weather events were also performed for current GOES and compared with available imagery for quality control purposes. Future work focuses on the creation of additional fire proxy datasets including true-color imagery for 3 ABI visible bands. This project also supports the GOES-R AWG Aviation Team in their effort to test their convective initiation algorithm by providing simulated ABI datasets for bands between 2.25 μm and 13.3 μm for a severe weather case. In addition, simulated ABI was generated from MSG infrared (IR) window band imagery and corresponding simulated ABI for the 7 tropical cyclones from 2006-2008 that became hurricanes in the east Atlantic for evaluation of the GOES-R ADT algorithm conducted by the University of Wisconsin Cooperative Institute for Meteorological Satellite Studies (CIMSS).

Northrop Grumman Aerospace Systems (NGAS) has developed the Hyperspectral Airborne Tactical Instrument (HATI), a compact airborne hyperspectral imager designed to fly on a variety of platforms and to be integrated with other sensors in the NGAS instrument suite. HATI has taken part in a variety of missions and flown in conjunction with other NGAS airborne sensors including the recently-developed NGAS 3-D flash ladar system to demonstrate a multi-sensor data fusion approach. HATI is a push-broom sensor which gathers information in the 400 nm to 1700 nm wavelength range. Its compact size allows HATI to be mounted on commercial-of-the-shelf (COTS) aerial photography stabilization platforms and on a large variety of aerial platforms. In its most recent flight season, the HATI sensor was used to gather data for applications including remote classification of vegetation, forests, and man-made materials. The HATI instrument has undergone laboratory and in-situ performance validation and radiometric calibration. This paper describes the HATI sensor and recent data collection campaigns.

Conventional space sensors have traditionally used CCD image sensors. Since CCD sensors provide analog output signals, the camera system has needed to integrate additional analog and digital circuitry including CCD drivers. The result is a camera that weighs more than 30 kg and dissipates more than 10 Watts of power. We report using an advanced semiconductor technology to integrate CMOS image sensors, analog and digital circuitry together into a single silicon chip. A Terrain Mapping Camera (TMC) was designed using this approach. The entire camera weighs less than 7 kg and dissipates only 1.8 Watts of power. The TMC was recently launched into moon orbit on October 22, 2008 aboard Chandrayaan-1. The image quality sent back from the TMC is excellent. Radiation testing of the digital image sensor was conducted prior to launch with the device enduring more than 300 kilo-rads.

Environmental remote sensing systems, currently being developed, carry multiple remote sensing sensors on a single spacecraft platform, producing dozens of weather data products with hundreds of attributes in quasi-real time. In this paper we present a capability to simulate the various components of such a system in order to predict the quality of the data products, as well as assess the impact of changing design parameters on the accuracy of the weather data. Such a detailed simulation tool is essential to systems producing scientific data products whether it is remote sensing of weather products or chemical and biological products. It is valuable during the design phase to ensure the system design produces the expected performance, during the verification phase to ensure the system as built will meet the specified performance, and during on-orbit calibration and validation phase to validate the performance of the deployed system.

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. The National Imagery Interpretability Rating Scale (NIIRS) is a useful measure of image quality, because, by characterizing the overall interpretability of an image, it combines into one metric those contributors to image quality to which a human interpreter is most sensitive. The main drawback to using a NIIRS rating as a measure of image quality in engineering trade studies is the fact that it is tied to the human observer and cannot be predicted from physical principles and engineering parameters alone. The General Image Quality Equation (GIQE) of Leachtenauer et al. 1997 [Appl. Opt. 36, 8322-8328 (1997)] is a regression of actual image analyst NIIRS ratings vs. readily calculable engineering metrics, and provides a mechanism for using the expected NIIRS rating of an imaging system in the design and evaluation process. In this paper, we will discuss how we use the GIQE in conjunction with The Aerospace Corporation's Parameterized Image Chain Analysis & Simulation SOftware (PICASSO) to evaluate imager designs, taking a hypothetical high resolution commercial imaging system as an example.

In the design process of Laser radar applications the scatter cross section of small objects like bullets is a basic problem. An estimation of detection rates depends strongly on the amount of light power reflected to the receiver as well as on the deliverable information about the objects geometry. Since very little information on Lidar cross sections of basic geometries in question is available - except for some exemplary experimental data - typical body shapes have been investigated. For simplicity, the two main cases, perfectly reflecting surfaces and Lambertian surfaces, are treated analytically, so a real body with direct and diffuse reflection in arbitrary weighting can be modeled. As a result, the amount of power reflected to the receiver as well as the actual image of the object gathered by an imaging device can be predicted. A mathematical estimation framework for the treatment of arbitrary bodies is developed, based on analytical and numerical methods and a set of basic cases, resulting in several rules of thumb. Besides the theoretical part, some illustrating experimental results are given..

A demodulation method for a quasi-distributed sensor based on an original interrogating system for concatenated low reflective Fiber Grating is proposed. The system is based on Optical Frequency Domain Reflectometer technology for which a commercial device has been extended to a wavelength-tunable device. This interrogation system has the advantage of allowing a large number of gratings to be addressed simultaneously. In our application, except of the first grating (it has 20 times higher reflective than others) all other gratings have low reflective (about 0.5% and 1 nm bandwidth at 3 dB) and have a Fiber Bragg Grating central wavelength of about 1535 nm. Compare to conventional Optical Frequency Domain Reflectometer technology, this interrogating system has very fast measurement capability and higher precision.