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This PDF file contains the front matter associated with SPIE Proceedings Volume 7689, including the Title Page, Copyright information, Table of Contents, Introduction, and the Conference Committee listing.
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The research described in this paper explores the addition of conformally integrated traffic probes into an egocentric
Synthetic Vision (SV) Primary Flight Display (PFD). The underlying thought is that, although the traffic that is predicted
to cause a future loss of separation may not lie within the field of view of the display, the location where the loss of
separation is predicted to occur always will. Hence, rather than focusing on the depiction of traffic, which contributes to
level 2 Situation Awareness (SA), the concept pursues spatially integrated depiction of the airspace where a loss of
separation is predicted. This provides readily actionable conflict information, relieving pilots from the traffic position
and conflict estimation task and contributing to level 3 SA. The paper describes the integration of the data from the
traffic probe into an SV PFD. The advantages of the concept will be illustrated using several traffic conflict scenarios,
including an overtaking scenario involving unmanned aircraft. Given that unmanned aircraft may be markedly slower
than manned aircraft which operate within the same airspace, a spatially integrated depiction of airspace where a future
loss of separation is predicted, can help to preserve safety in classes of airspace that accommodate both manned and
unmanned aircraft. Additionally, examples are provided illustrating how traffic probes can support pilots in monitoring
the conformance of traffic to the priority rules of 14 CFR 91.113.
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Recent research in Synthetic/Enhanced Vision technology is analyzed with respect to existing Category II/III
performance and certification guidance. The goal is to start the development of performance-based vision systems
technology requirements to support future all-weather operations and the NextGen goal of Equivalent Visual Operations.
This work shows that existing criteria to operate in Category III weather and visibility are not directly applicable since,
unlike today, the primary reference for maneuvering the airplane is based on what the pilot sees visually through the
"vision system." New criteria are consequently needed. Several possible criteria are discussed, but more importantly,
the factors associated with landing system performance using automatic and manual landings are delineated.
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During Apollo, the constraints placed by the design of the Lunar Module (LM) window for crew visibility and
landing trajectory were "a major problem." Lunar landing trajectories were tailored to provide crew visibility
using nearly 70 degrees look-down angle from the canted LM windows. Apollo landings were scheduled only at
specific times and locations to provide optimal sunlight on the landing site.
The complications of trajectory design and crew visibility are still a problem today. Practical vehicle designs
for lunar lander missions using optimal or near-optimal fuel trajectories render the natural vision of the crew
from windows inadequate for the approach and landing task. Further, the sun angles for the desirable landing
areas in the lunar polar regions create visually powerful,
season-long shadow effects. Fortunately, Synthetic and
Enhanced Vision (S/EV) technologies, conceived and developed in the aviation domain, may provide solutions to
this visibility problem and enable additional benefits for safer, more efficient lunar operations. Piloted simulation
evaluations have been conducted to assess the handling qualities of the various lunar landing concepts, including
the influence of cockpit displays and the informational data and formats. Evaluation pilots flew various landing
scenarios with S/EV displays. For some of the evaluation trials, an eye glasses-mounted, monochrome monocular
display, coupled with head tracking, was worn. The head-worn display scene consisted of S/EV fusion concepts.
The results of this experiment showed that a head-worn system did not increase the pilot's workload when
compared to using just the head-down displays. As expected, the
head-worn system did not provide an increase in
performance measures. Some pilots commented that the head-worn system provided greater situational awareness
compared to just head-down displays.
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Input, management, and display of taxi routes on airport moving map displays (AMM) have been covered in various
studies in the past. The demonstrated applications are typically based on Aerodrome Mapping Databases (AMDB). Taxi
routing functions require specific enhancements, typically in the form of a graph network with nodes and edges modeling
all connectivities within an airport, which are not supported by the current AMDB standards. Therefore, the data
schemas and data content have been defined specifically for the purpose and test scenarios of these studies.
A standardization of the data format for taxi routing information is a prerequisite for turning taxi routing functions into
production. The joint RTCA/EUROCAE special committee SC-217, responsible for updating and enhancing the AMDB
standards DO-272 [1] and DO-291 [2], is currently in the process of studying different alternatives and defining
reasonable formats.
Requirements for taxi routing data are primarily driven by depiction concepts for assigned and cleared taxi routes, but
also by database size and the economic feasibility. Studied concepts are similar to the ones described in the GDF
(geographic data files) specification [3], which is used in most car navigation systems today. They include
- A highly aggregated graph network of complex features
- A modestly aggregated graph network of simple features
- A non-explicit topology of plain AMDB taxi guidance line elements
This paper introduces the different concepts and their advantages and disadvantages.
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We present the design and first field trial results of the all-day all-weather INVIS Integrated Night Vision surveillance
and observation System. The INVIS augments a dynamic three-band false-color nightvision image with synthetic 3D
imagery in a real-time display. The night vision sensor suite consists of three cameras, respectively sensitive in the visual
(400-700 nm), the near-infrared (700-1000 nm) and the longwave infrared (8-14 μm) bands of the electromagnetic
spectrum. The optical axes of the three cameras are aligned. Image quality of the fused sensor signals can be enhanced
in real-time through Dynamic Noise Reduction, Superresolution, and Local Adaptive Contrast Enhancement. The
quality of the longwave infrared image can be enhanced through Scene-Based Non-Uniformity Correction (SBNUC),
intelligent clustering and thresholding. The visual and near-infrared signals are used to represent the resulting multiband
nightvision image in realistic daytime colors, using the Color-the-Night color remapping principle. Color remapping can
also be deployed to enhance the visibility of thermal targets that are camouflaged in the visual and near-infrared range of
the spectrum. The dynamic false-color nighttime images can be augmented with corresponding synthetic 3D scene
views, generated in real-time using a geometric 3D scene model in combination with position and orientation
information supplied by the GPS and inertial sensors of the INVIS system.
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DLR's Institute of Flight Guidance is involved in many projects dealing with the development of new concepts
for flight procedures and pilot assistance functions. This includes especially the topic of enhanced vision (EVS),
where processed data from radar and infrared sensors is utilized to augment the pilot's vision. For evaluating
these concepts extensive flight testing has been conducted and results have been published during the last years.
Now, DLR has combined its expertise in the field of high performance sensor simulation on the one hand side,
together with the visual simulation for its generic cockpit simulator, on the other hand. Sensor simulation of
imaging radar, lidar, infrared, etc., is based mainly on the application of high performance functions of modern
computer graphics hardware (vertex and fragment shaders). The direct combination of these functions with the
"outside-vision" software, which is now based on exactly the same terrain and object geometry, delivers sensor
data that perfectly correlate to the visual channel. This combined simulation environment will be the basis
for various evaluation trials within the near future, including simulation trails for fixed-wing and rotary-wing
applications.
The paper presents the implemented software and hardware architecture of the cockpit's visual simulator and its
coupling to the sensor simulation test-suite. First results of recently conducted simulation experiments including
the evaluation of new proposed flight procedures, which apply EVS technology, are given.
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Accurate image registration is a pre-requisite for most systems utilising two or more imaging sensors. This can often be
accomplished off-line in the laboratory using appropriate test targets and calibration sources but achieving and
maintaining registration accuracy automatically in the field is a significant challenge. This paper presents an efficient
image registration algorithm capable of automatically registering dual waveband image streams upon system start-up and
then producing updated transform coefficients during live operation. The algorithm is fully automatic and constrained to
ensure reliable operation with minimal or no operator supervision. Robustness to large initial alignment errors is
demonstrated using a selection of challenging multimodal image sets. In addition, a novel high performance adaptive
image fusion algorithm for maximising fused image quality in the presence of sensor noise is presented.
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We present the design and first field trial results of the INVIS integrated night vision surveillance and observation
system, in particular for the image enhancement techniques implemented. The INVIS is an all-day-andnight
all-weather navigation and surveillance tool, combining three-band cameras. We present a processing
pipeline for this system. The image quality of all individual sensor signals is enhanced through Dynamic Noise
Reduction and Dynamic Super Resolution. The quality of the thermal image can be enhanced through
Scene-Based Non-Uniformity Correction (SBNUC). The images are fused using natural tone mapping techniques.
The contrast in the image can be improved using Local Adaptive Contrast Enhancement, applied before or
after the tone mapping. These results show that the image enhancement techniques have an added value for
image fusion systems.
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A color transfer method is presented to give fused multiband nighttime imagery a natural daytime color appearance in a
simple and efficient way. Instead of using the traditional nonlinear lαβ space, the proposed method transfers the color
distribution of the target image (daylight color image) to the source image (fused multiband nighttime imagery) in the
linear YCBCR color space. The YCBCR transformation is simpler and more suitable for image fusion compared to the lαβ
conversion. The YCBCR transformation can be extended into a general formalism. And the paper mathematically proves
that, for color transfer, using color spaces conforming to this general YCBCR space framework can produce same
recoloring results as using the YCBCR space. Experimental results demonstrate that the YCBCR based color transfer
method works surprisingly well for transferring natural color characteristics of daylight color images to false color fused
multiband nighttime imagery, and moreover, can also be successfully applied to recoloring a variety of color images.
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When used in conjunction with helmet mounted displays stereo camera views can provide invaluable advantages
in, for example, aviation uses. One of the most common setups is to mount cameras to both sides of the pilot's
helmet. However, since these cameras posses a larger disparity than the eyes distances to perceived objects are
misinterpreted by the pilot. This may cause irritations, even sickness when combined with enhanced displays.
Even in the best case the magnified disparity may lead to exaggerated distance estimations. In this paper simple
computations are presented that can correct hyperstereopsis "on the fly". With the availability of fast computer
hardware carrying out these computations in real time comes into reach. Furthermore, we sketch a series of
experiments to evaluate the effectiveness of our approach.
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Degraded visual conditions can marvel the curious and destroy the unprepared. While navigation instruments are
trustworthy companions, true visual reference remains king of the hills. Poor visibility may be overcome via imaging
sensors such as low light level charge-coupled-device, infrared, and millimeter wave radar. Enhanced Vision systems
combine this imagery into a comprehensive situation awareness display, presented to the pilot as reference imagery on a
cockpit display, or as world-conformal imagery on head-up or
head-mounted displays.
This paper demonstrates that Enhanced Vision imaging can be achieved at video rates using typical CPU / GPU
architecture, standard video capture hardware, dynamic non-linear ray tracing algorithms, efficient image transfer
methods, and simple OpenGL rendering techniques.
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This paper discusses an alternative ADS-B implementation that uses available provisions (Mode-S, UAT and GPS
receivers) and existing GPS algorithms and techniques. This alternative has many advantages over the current ADS-B
implementation, especially with respect to integrity of the solution. The paper will describe the methodology, its
advantages, simulation results and implementation issues.
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Resolution is often provided as one of the key parameters addressing the quality characteristic of a sensor. One
traditional approach when determining the resolution of a sensor/display system is to use a resolution target pattern to
detect the smallest element that can be "resolved" using the system. This requires a human in the loop to make the
assessment. This study investigated the use of a custom designed software approach to generate an effective resolution
value for a sensor. Landolt Cs were selected as the resolution target, which were imaged at multiple distances with
different sensors. The images were analyzed using custom software to determine the orientation of the C at each
distance, which resulted in a probability of correct orientation detection curve as a function of distance. This curve was
used to generate a "resolution" for the sensor without involving human vision. Resolution results for four different
spectral band sensors were obtained as well as effective resolution of fused images from select pairs of sensors. These
results and the possible use of this synthetic observer resolution approach are presented and discussed, as well as
possible future research relating this resolution to human visual performance with fused image sources.
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This paper discusses the results of an initial evaluation study of hazard and integrity monitor functions for use with
integrated alerting and notification. The Hazard and Integrity Monitor (HIM) (i) allocates information sources within the
Integrated Intelligent Flight Deck (IIFD) to required functionality (like conflict detection and avoidance) and determines
required performance of these information sources as part of that function; (ii) monitors or evaluates the required
performance of the individual information sources and performs consistency checks among various information sources;
(iii) integrates the information to establish tracks of potential hazards that can be used for the conflict probes or conflict
prediction for various time horizons including the 10, 5, 3, and <3 minutes used in our scenario; (iv) detects and assesses
the class of the hazard and provide possible resolutions. The HIM monitors the operation-dependent performance
parameters related to the potential hazards in a manner similar to the Required Navigation Performance (RNP). Various
HIM concepts have been implemented and evaluated using a previously developed sensor simulator/synthesizer. Within
the simulation framework, various inputs to the IIFD and its subsystems are simulated, synthesized from actual collected
data, or played back from actual flight test sensor data. The framework and HIM functions are implemented in
SimulinkR, a modeling language developed by The MathworksTM. This modeling language allows for test and
evaluation of various sensor and communication link configurations as well as the inclusion of feedback from the pilot
on the performance of the aircraft.
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The objective of the project ALLFlight (Assisted Low Level Flight and Landing on Unprepared Landing Sites) is to
demonstrate and evaluate the characteristics of different sensors for helicopter operations within degraded visual
environments, such as brownout or whiteout. The sensor suite, which is mounted onto DLR's research helicopter EC135
consists of standard color or black and white TV cameras, an un-cooled thermal infrared camera (EVS-1000, Max-Viz,
USA), an optical radar scanner (HELLAS-W, EADS, Germany) and a millimeter wave radar system (AI-130, ICx Radar
Systems, Canada). Data processing is designed and realized by a sophisticated, high performance sensor co-computer
(SCC) cluster architecture, which is installed into the helicopter's experimental electronic cargo bay.
This paper describes applied methods and the software architecture in terms of real time data acquisition, recording, time
stamping and sensor data fusion. First concepts for a pilot HMI are presented as well.
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In bad weather conditions, with the presence of haze, fog or smoke, atmospheric particles attenuate the direct irradiance
from the scene and scatter light to form airlight. Thus, visibility is decreased and may endanger important applications,
such as outdoor surveillance or visual navigation for landing and taking off aircrafts. This paper proposes a novel method
for visibility enhancement in bad weather conditions based on
multi-view camera system. The main advantage of this
method lies in the ability to solve ambiguities caused by
texture-less, lack of color and contrast, while where most
existing methods fail.
The proposed system consists of two main components. First is a
data-driven approach to extract template priors that are
matched with current capturing dynamic scene images. A fixed
multi-camera system is utilized to record dynamic scene
appearances under different illuminations, in different time, seasons and weather conditions to construct the database
which is explored to extract template models containing only static background objects and obtain corresponding scene
structures in a data-driven manner. Second is dehazing based on current dynamic scene depth updated by fusing template
depth with real-time multi-view stereo matching depth in foreground object regions.
The proposed system achieves real-time and robust performances through combinations of data-driven prior extraction
and dynamic scene depth optimization. Moreover, estimated weather condition parameters and the real-time
reconstructed dynamic scene model are both useful byproducts. We believe that the proposed system is the first to
dehaze based on multi-view camera system. An application based on airport surveillance demonstrates its effectiveness.
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