The work discussed in this Final Report was part of a planned three-year project which included these major tasks:
1. Develop improved sensor models and hazard metrics;
2. Validate models and simulations by comparing predicted results to empirical data; and 3. Conduct ground-based field measurements focused on mountain waves and CAT.
Each of these three tasks is summarized by Year in the subsections below. Our technical accomplishments during the entire project are described in detail in the remainder of this report.
2.1 Year 1 Summary
This section of the report gives a brief summary of work completed in Year 1 [18].
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Runway Surface Conditions and Obstructions: In the first year several ground-based measurements were conducted. These ground-based measurements included iced and wet asphalt/concrete; runway surroundings such as terrain; and wildlife (with another LWIR imager).
Low Visibility Measurements: Unfortunately in Year 1 reduced visibility conditions, such as fog and smoke, were not present after acquisition of the Telops Hyper-Cam; these measurements were completed in Year 2.
ATL Wake Vortex Measurements: Year 1 included a small-scale ground-based data collection activity at Hartsfield-Jackson (ATL) with the Telops Hyper-Cam as a precursor to the full data collection for the detection of wake vortices that was originally planned for SFO in Year 3. The data collection activities were coordinated with personnel from ATL and Jacoby Development, the company that owns the property on which we were physically located during the data collection activity. Overall, three visits to ATL occurred in Years 1 and 2.
Plan SFO Wake Vortex Measurements: Planning for the larger-scale data collection activity in SFO began; however, during the WakeNet Conference, it was learned that the SFO WindTracer Lidar was temporarily inoperable and that ATL had a WindTracer installed. Financially, operationally, and logistically it made sense to have the data collection activity in ATL.
Therefore, the field test was officially moved from SFO to ATL.
Model Validation: Several activities that underlie model validation and updates occurred during Year 1; this, however, is an ongoing process. These activities included wake vortex simulations for comparison with actual data, Line-by-Line Radiative Transfer Model (LBLRTM) calculations, and a Fast Forward Model Development.
Wake Vortex Model Simulations: Hyper-Cam radiance simulations were conducted with wake vortex model data provided by Dr. Fred Proctor. We analyzed data for heavy aircraft typical of what was observed by the Hyper-Cam during measurements conducted at ATL. Also, we used the model simulations to simulate what a FLI would see from an aircraft at 1 km altitude (i.e. on takeoff or landing behind a heavy commercial aircraft). Simulations show small sensitivity to the temperature and water vapor variability produced by a wake vortex.
Hyper-Cam Line-by-Line Radiative Transfer Model (LBLRTM) Calculations: LBLRTM calculations were performed using radiosonde measurements conducted from Peachtree City for comparisons with the sky viewing Hyper-Cam measurements made at GTRI on different occasions. These comparisons were used to evaluate the spectral and radiometric calibration accuracy of the Hyper-Cam measurements.
A Fast Forward Model Development: A Fast Forward Model (FFM) was developed to produce rapid calculations of Hyper-Cam radiances from atmospheric state conditions as well as for use in an inverse radiative transfer model for retrieving atmospheric state parameters from Hyper-Cam measurements. Comparisons with time-consuming Line-by-Line calculations indicate an accuracy of the FFM calculations close to the observational errors of the Hyper-Cam observations.
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Instrument Requirements: Development of instrument requirements was an ongoing task and was not specifically addressed in Year 1.
2.2 Year 2 Summary
This section of the report gives a brief summary of work completed in Year 2 [19].
Wake Vortices: Three separate field campaigns for the collection of wake vortex data were conducted at ATL during the summer and fall of 2010 (during Years 1 and 2) in preparation for a full-scale field campaign at either SFO or ATL (later determined to be ATL). The Telops Hyper-Cam was used to collect hyperspectral image data cubes. The main purpose of these tests was to test look angles, data collection parameters, and length of data collection episodes.
Additionally it was hoped that wake vortices could readily be seen in the data based on previous modeling and analysis.
Wake vortex data collected with the Telops Hyper-Cam at Hartsfield-Jackson International Airport (ATL) was analyzed by both the GTRI and Hampton University teams. Hyperspectral gas detection algorithms were used in an attempt to detect wake vortices by finding the exhaust gases they entrain. A methodology for the detection of wake vortices by utilizing these gas detection algorithms was presented; while the method does not detect vortices in the data, the directional averaging of sky radiance in the target/background modeling shows what appear to be vapor trails following the aircraft. The results were inconclusive as to whether the exhaust gases were actually being detected or some other disturbance was being seen. However, this method of breaking up the background demonstrates a novel way to detect mixed pixel targets against sky backgrounds; this method yielded results when other similar methods did not. The results warrant more study, since the possible detection of a turbulent effect, though not a vortex, is still relevant to the FLI program. This work was presented at SPIE in August 2011 [20].
Mountain Wave Turbulence: Turbulence associated with mountain waves came to the forefront of the remaining research effort for this program in place of wake vortices. Therefore, while always having been a part of the overall program, the main data collection field campaign was focused on detection of mountain waves. Analysis of previously collected hyperspectral data was re-visited and analyzed, new data for comparison was collected, and a site visit for Year 3’s field campaign near Boulder, CO was conducted.
Runway Surface State and Contamination: As a secondary priority, runway surface state and contamination was studied with hyperspectral imaging. Emissivity images, obtained from an aircraft-mounted Forward Looking Interferometer (FLI), are intended to be used to alert the pilot of hazardous landing runway surface conditions and enable the determination of runway friction and associated stopping distance for a particular aircraft. This hazard detection technique is based on the fact that different surfaces have different emissivity spectra in the LWIR spectral region, where the FLI operates. Ground-based measurements taken during Year 2 included: ice; snow;
wet/dry asphalt and concrete; and runway surroundings/hazards such as terrain, wildlife, and vehicles. Data was analyzed and a conference paper was presented at the Optical Society of America (OSA) Hyperspectral Imaging and Sounding of the Environment (HISE) conference in July 2011 [21].
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Low Visibility: As a secondary priority, reduced visibility conditions (such as fog) were exploited when they occurred to measure hyperspectral images of concrete/asphalt and buildings in these conditions. The main purpose of these measurements was to provide hyperspectral data to investigate a technique that was developed and reported in a previous phase of the FLI project.
The technique is aimed at mitigating reduced visibility during landings in obscured conditions.
2.3 Year 3 Summary
This section of the report gives a brief summary of work completed in Year 3 of the current FLI project [22].
Fast FLI Forward Radiative Transfer Model: Updates to the Fast FLI Forward Radiative Transfer Model (FLI-FM) and verification by comparison with Line-by-Line Radiative Transfer Model (LBLRTM) were completed. Much of the modeling and simulation, regardless of the hazard under investigation, was accomplished using the updated FLI-FM2.
Wake Vortices: An overview of infrared FTS for the detection of wake vortices was given during Year 3 in a brief summary from Taumi Daniels’ thesis [23]. Wake vortex models developed by Daniels using TASS and LBLRTM were described and are expanded to include FLI-FM2 simulations.
Mountain Wave Turbulence: Mountain wave turbulence was the main hazard under investigation during Year 3. Mountain wave turbulence FLI-FM models and simulations were completed in order to provide guidance for test planning at the Mountain Research Station (MRS). The data collection activity, which was designed in an effort to capture turbulent signals in the atmosphere over the Colorado Rockies, was completed in November 2011. Analysis of MRS data included data correction (including calibration issues, bad pixel replacement, and cloud removal), temporal variability analysis, gas detection analysis, and temporal anomaly analysis.
Runway Surface Conditions and Obstructions: The ability to detect the surface emissivity for various types of runway surface conditions with a FLI is important for the determination of runway friction and aircraft stopping distance. During Year 2, ground-based emissivity measurements were made of ice, snow, and wet/dry asphalt and concrete. The subsequent analysis of these measurements demonstrated a methodology for the detection of hazardous surface conditions; however, the ice and concrete measurements were set up (i.e. artificial man-made conditions, not natural ice). Only one opportunity for measurements of natural ice and snow occurred during Year 2, but it was not fresh (the snow had iced over). During Year 3, the opportunity arose to make the same measurements in a natural environment that was more representative of a hazardous runway condition.
Volcanic Ash: Detection of volcanic ash has not been investigated by the FLI team, as methods of modeling the movement of volcanic ash (PUFF model) and instruments for its detection (Airborne Hazards Detection System, Norwegian Institute for Atmospheric Research) already exist. A summary of the relevant literature and patents was given.
Distance to the Hazard: The ability to determine the distance to a hazard relies on the collection of high spectral resolution data (1 cm-1). Over the last year, we have shifted to lower spectral
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resolution data (16 cm-1) to try to detect the signal of the hazards. As such, we have inherently lost the ability to determine the distance to the hazard using the CO2 line structure. However, an additional dedicated detector with two narrowband filters that can look at the amplitudes of the CO2 lines has been proposed. Note that these lines appear in the mid-wave infrared (MWIR).
Detection has focused on the long-wave infrared (LWIR). Therefore a dedicated detector would be in the MWIR, while the hazard detection detector would be in the LWIR.