This PDF file contains the front matter associated with SPIE Proceedings Volume 11424, including the Title Page, Copyright information, and Table of Contents.

Degraded visual environments are a cause of problems for surveillance systems and other sensors due to the reduction in contrast, range, and signal. Fog is a concern because of the frequency of its formation along our coastlines; disrupting border security and surveillance. Sandia has created a Fog Facility for the characterization and testing of optical and other systems. We will present a comparison of our generated fogs to the measured naturally occurring fogs reported in the literature and an overview of Sandia’s work using this facility to investigate ways to enhance perception through degraded visual environments.

This paper describes progress in the ongoing development of a radar for rotorcraft that utilizes new CMOS ICs that were development for automotive applications. The radar design is discussed, including a lens-based focal plane array that is fed by patch antenna subarray elements. Measured detection pattern data indicates sensitivity sufficient to detect a 1 m2 RCS object at 200 m with a 13dB SNR. Detection pattern data vs. azimuth angle are presented, which indicate a 2.1 deg 3dB beamwidth. Sidelobes are reduced to 30dB below the beam peaks using digital beamforming techniques.

This communication reports progress towards the development of computational sensing and imaging methods that utilize highly scattered light to extract information at greater depths in degraded visual environments like fog for improved situational awareness. As light propagates through fog, information is lost due to random scattering and absorption by micrometer sized water droplets. Computational diffuse optical imaging shows promise for interpreting the detected scattered light, enabling greater depth penetration than current methods. Developing this capability requires verification and validation of diffusion models of light propagation in fog. We report models that were developed and compared to experimental data captured at the Sandia National Laboratory Fog Chamber facility. The diffusion approximation to the radiative transfer equation was found to predict light propagation in fog under the appropriate conditions.

It is highly desired that modern navigational systems work accurately and reliably not only in the situations where a GPS signal is available but also in the situations where GPS signal is not present or is artificially jammed. In many GPS restricted situations, such as indoors, caves, canyons or GPS jamming situations, traditional navigation systems fail to operate. Nowadays, many researchers propose multiple solutions to overcome these limitations. Amongst different solutions for solving GPS-denied navigation, Visual-Inertial Odometry (VIO) gets significant attention in the research community. However, due to significant computational requirements and insufficient robustness while handling complex real life situations, only a small subset of the proposed solutions can provide desirably accurate results and be considered for applications where acceptable Size, Weight, and Power (SWaP) are limited. In this paper, we compare accuracy and robustness of several popular, open-source algorithms and Commercial Off-The-Shelf (COTS) VIO systems potentially suitable for SWaP-limited platforms and applicable for wearable-type applications.

The Boeing Research &Technology’s All-Source PNT open architecture employs a wide range of sensors to provide navigation in A2AD/GPS-Denied environments. The system using a Phantom-Fusion3 open architecture based processor is currently configured in a POD and is being flight tested employing LWIR (Long Wave Infrared) high resolution cameras that is incorporating pattern matching algorithms that compares USGS (United States Geological Survey) maps (or equivalent) to real-time test data to provide navigation updates without GPS. We are currently building a navigation radar that will additionally will be flight tested and is expected to begin testing this year (2020). Additionally, Gravity Anomaly will be field tested to evaluate its potential. Signals of Opportunity (SOO) testing using LEO satellites is expected in 2020.

Today's ISR (Intelligence, Surveillance and Reconnaissance) defense coalitions require storage and dissemination mechanisms that are able to cope with emerging changes to requirements and new features. Previous System of systems (SOS) architectures used to be built with years of planning, development, testing and deployment, usually in the form of distributed monoliths. Due to new requirements in ISR, shorter response cycles are required. To reach this goal, new approaches are of interest in the architectural style and workload sharing within the development team, resulting in the ability to better maintain and change existing software solutions. Ideally, such a shift results in improved scalability, replaceability, modularity and resilience. In this context we examined our existing software that provides and also internally uses legacy middleware such as Common Object Request Broker Architecture" (CORBA) (among others). The overall codebase was written in such a manner that it was easy to produce, i.e., technically motivated. The development team is rather small, so efficiency and the possibility to share (developer) knowledge is important. Our goal was to evaluate the state of the art, thus being able to reasonably apply modern software development approaches that support mandatory legacy support. We attempted a restructuring of the codebase applying the principles of Domain-Driven Design" with its bounded contexts", resulting in domain-oriented source code that is easy to verify and maintain. Keeping in mind our small development team, we aimed for shared responsibility, giving us the necessary resilience for unplanned staff absence. In this publication, we present a possible migration path with its operational constraints (e.g., legacy inter-

This paper reports on a software architecture designed for multi-sensor pilotage displays. A need existed for a graphical display that was highly flexible and reusable between sensor systems. To that end, we developed a graphical rendering system based on scene graph architecture, which allows nodes to be added and removed, depending on the needs of the sensor and display system. Individual users and organizations can develop and apply their own nodes to this architecture while maintaining compartmentalization of intellectual property. We applied this software architecture to a radar sensor pilotage display for a rotorcraft in a degraded visual environment, based on layered extensions of the ICE / BOSS symbology set, as well as standard MIL-STD-2525 symbology. In this paper, we report the results of the software architecture development effort, and outline the rationale behind the design decisions that were made in the development process.

Searching and tracking at night can be enhanced using flashlights and body-mounted lamps with optimized illumination spectra while using less battery power. Benefits include improved situational awareness and more rapid identification of important detail, hazards, and surface conditions (e.g., water, ice, or oil films) for a wide range of both military and civilian personnel. Many complex natural surfaces appear as dark brown, grey, or black. Small spectral differences can be critically important for the identification of surface structures and objects. Improved visual object detail recognition is possible if differential color can be enhanced. Over 18,000 reflected spectral data measurements from natural terrestrial objects such as recently disturbed soils, ground clutter, foliage, bark, fungi, minerals, blood, and a wide variety of ground hazards have been collected and analyzed to predict the optimal spectra illumination for the tasks of visually differentiating color, topology, and detail in natural terrestrial objects and many other surfaces. This paper relates and summarizes a vast amount of reflected light data with human visual sensitivity. We found that broad-spectrum, over-90 CRI LED light sources with boosted cyan (480-510nm) and a wide range of visible reds (610-700nm) can better highlight differences in many darker-shade objects and most other surfaces better than cool-white, neutral, or warm-white LED flashlights and head-worn lamps typically used today even though the perceived “brightness” in lumens is lower for a given amount of illumination power.

Monocular augmented reality devices are used in aviation to help civilian or military pilots in their flying task. Given that the image is presented in front of only one eye, the two eyes are not stimulated in the same way and it can create a phenomenon known as binocular rivalry. It appears when the brain is not able to merge the two visuals information and an alternation between them can occur. This alternation is dependent on visual condition and the question arises as is it relevant to choose the eye to display the image to limit binocular rivalry and guarantee a good performance in the tasks of recognition and control. Our study aims to compare the performances as a function of the position of the virtual image. These results are then compared to the results of several dominant eye tests to determine if one test can objectively determine on which eye the monocular information should be displayed when using a monocular see-through device.

Dengue is the most common mosquito-transmitted diseases, leading to millions of serious illnesses and deaths each year. Because the mosquito vectors are sensitive to environmental conditions such as temperature, precipitation, and humidity, it is possible to map areas currently or imminently at high risk for disease outbreaks using satellite remote sensing. In this paper we propose the development of an operational geospatial system for Dengue and dengue fever early warning; this can be done by bringing together geographic information system (GIS) tools, artificial neural networks (ANN) for efficient pattern recognition, the best available ground-based epidemiological and vector ecology data, and current satellite remote sensing capabilities. We use Vegetation Health Indices (VHI) derived from visible and infrared radiances measured by satellite-mounted Advanced Very High Resolution Radiometers (AVHRR) and available weekly at 4-km resolution as one predictor of dengue fever risk in Bangladesh. As a study area, we focus on Bangladesh where dengue fever are serious public health threats. The technology developed will, however, be largely portable to other countries in the world and applicable to other disease threats. A dengue fever early warning system will be a boon to international public health, enabling resources to be focused where they will do the most good for stopping pandemics, and will be an invaluable decision support tool for national security assessment and potential troop deployment in regions susceptible to disease outbreaks.