PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
This PDF file contains the front matter associated with SPIE
Proceedings Volume 8403, including the Title Page, Copyright
information, Table of Contents, and the Conference Committee listing.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
Semiconductor optical amplifiers are important for wide range of applications in optical networks, optical tomography
and optical logic systems. For many of these applications particularly for optical networks and optical logic, high speed
performance of the SOA is important. All optical Boolean operations such as XOR, OR, AND and NOR has been
demonstrated using SOA based Mach-Zhender interferometers (SOA-MZI). A rate equation model for SOA-MZI has
been developed. The model has been used to analyze the Set-Reset (S-R) latch, the gated S-R latch and the D-Flip-Flop
devices. The modeling results suggest that the Flip-Flop circuits should work at high speeds. An optical pseudo-random
bit stream (PRBS) generator is important for all-optical encryption circuits. A model of a PRBS generator using SOAMZI
based devices has been developed. We show that a PRBS generator can work @ 80 Gb/s using regular SOAs and
@ ~ 250 Gb/s or at higher speeds using two-photon absorption based processes in SOAs.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
The increasing use of infrared sensors requires development of advanced infrared training and simulation
tools to meet current Warfighter needs. In order to prepare the force, a challenge exists for training and
simulation images to be both realistic and consistent with each other to be effective and avoid negative
training. The US Army Night Vision and Electronic Sensors Directorate has corrected this deficiency by
developing and implementing infrared image collection methods that meet the needs of both real image
trainers and real-time simulations. The author presents innovative methods for collection of high-fidelity
digital infrared images and the associated equipment and environmental standards. The collected
images are the foundation for US Army, and USMC Recognition of Combat Vehicles (ROC-V) real image
combat ID training and also support simulations including the Night Vision Image Generator and Synthetic
Environment Core. The characteristics, consistency, and quality of these images have contributed to the
success of these and other programs. To date, this method has been employed to generate signature
sets for over 350 vehicles. The needs of future physics-based simulations will also be met by this data.
NVESD's ROC-V image database will support the development of training and simulation capabilities as
Warfighter needs evolve.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
The development and testing of thermal signature tracking algorithms burdens the developer with a method o f testing the
algorith m's fidelity. Collected video is normally used for testing tracking algorithms to evaluate performance in a variety
of configurations. Acquiring suitable volumes of collected video data in multiple configurations can be prohibitive. As
an alternative to collected video, the development of accurate synthetic thermal infrared vehicle models are incorporated
into background infrared scenes generated using the Digital Image and Remote Sensing Image Generat ion (DIRSIG)
software package. Additional software models for thermally emissive targets and motion are being implemented. The
goals are to accurately incorporate thermal signatures of moving targets into realistic radiomet rically calibrated scenes.
This aids in evaluating tracking algorithms using both visible and thermal infrared signatures for improved day and night
detection capability. The software packages are integrated together to produce synthetic video.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
Effective use of passive and active sensors for surveillance, security, and intelligence must consider terrain and
atmospheric effects on the sensor performance. Several years ago, U.S. Army ERDC undertook development of software
for modeling environmental effects on target signatures, signal propagation, and battlefield sensors for many signal
modalities (e.g., optical, acoustic, seismic, magnetic, radio-frequency, chemical, biological, and nuclear). Since its
inception, the software, called Environmental Awareness for Sensor and Emitter Employment (EASEE), has matured
and evolved significantly for simulating a broad spectrum of signal-transmission and sensing scenarios. The underlying
software design involves a flexible, object-oriented approach to the various stages of signal modeling from emission
through processing into inferences. A sensor placement algorithm has also been built in for optimizing sensor selections
and placements based on specification of sensor supply limitations, coverage priorities, and wireless sensor
communication requirements. Some recent and ongoing enhancements are described, including modeling of active
sensing scenarios and signal reflections, directivity of signal emissions and sensors, improved handling of signal feature
dependencies, extensions to realistically model additional signal modalities such as infrared and RF, and XML-based
communication with other calculation and display engines.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
We present the study of two important trade-offs in heterogeneous systems (i.e., between performance versus portability
and between performance and accuracy) for a relevant linear algebra problem, matrix multiplication modulo primes. Integer
matrix linear algebra methods rely heavily on matrix multiplication modulo primes. Double precision is necessary for exact
representation of sufficiently many primes. We examine the performance losses due to the use of OpenCL versus CUDA
and the use of double versus single precision. Our results indicate that performance losses from the former are minimal
with the benefit of cross-platform portability and from the latter are acceptable when double precision is required.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
ArrayFire is a GPU matrix library for the rapid development of general purpose GPU (GPGPU) computing applications
within C, C++, Fortran, and Python. ArrayFire contains a simple API and provides full GPU compute
capability on CUDA and OpenCL capable devices. ArrayFire provides thousands of GPU-tuned functions including
linear algebra, convolutions, reductions, and FFTs as well as signal, image, statistics, and graphics libraries.
We will further describe how ArrayFire enables development of GPU computing applications and highlight some
of its key functionality using examples of how it works in real code.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
Lee A. Hendrix, Jack Calman, Brian M. Fisher, Stephen W. Kay, Christopher M. Lavelle, Robert M. Mayo, Bruce E. Miller, Katherine M. Ruben, Roger L. West
Proceedings Volume Modeling and Simulation for Defense Systems and Applications VII, 84030D (2012) https://doi.org/10.1117/12.921463
The acquisition of systems to locate and interdict Special Nuclear Material (SNM) is significantly enhanced when trade
space analysis of and CONOPS development for various proposed sensor systems is performed using realistic
operational scenarios in a synthetic simulation environment. To this end, the U. S. Defense Threat Reduction Agency
(DTRA) has developed a collaborative constructive simulation environment hosted at the DTRA Center at Ft. Belvoir,
VA. The simulation environment includes a suite of modeling and simulation (M&S) tools, scenario vignette
representations, geographic information databases, and authoritative sensor system representations. Currently focused on
modeling the detection and interdiction of in-transit SNM, the M&S tools include the Monte Carlo N-Particle (MCNP)
simulation for detailed nuclear transport calculations and the JHU/APL enhanced Joint Semi-Automated Forces (JSAF)
synthetic simulation environment and several associated High-Level Architecture (HLA) federate simulations for
engagement-level vignette executions. This presentation will focus on the JHU/APL enhancements to JSAF which have
enabled the execution of SNM detection vignettes. These enhancements include the addition of a user-configurable
Radioactive Material (RM) module for representation of SNM objects, a user-configurable RM Detection Module to
represent operational and notional gamma and neutron detectors, a Radiation Attenuation Module to calculate net
emissions at the detector face in the dynamic JSAF environment, and an RM Stimulation Module to represent notional
proton and photon beam systems in active interrogation scenarios.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
Data Modeling is a process that can convert non-real-time algorithms into functional approximations that can be
executed in near real-time as platform independent mathematical equations or information transfer functions. These
functional approximations are converted into a form amenable for streaming real-time execution by being converted into
pre-calculated look-up table (LUT) form. We present the technique and relevant theory and demonstrate how this
method can be applied to high level interactions, system level modeling and component modeling using a common
framework. An important benefit of our technique is the ability to predict anomalous parameters from our models.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
This paper presents a method that integrates Modeling and Simulation (M&S) Verification and Validation (V&V) as part
of the M&S design. Experience indicates that in the past, very few models were developed with V&V as part of the
design process. Formal V&V was usually done after the model had been released to the user community and was being
used by major programs to support major decisions. This has changed in recent years as declining resources have
resulted in a growing reliance on M&S. As awareness of the issues and the risks involved has increased, Department of
Defense (DoD) policies have been written that require V&V to be implemented as part of the M&S design, development,
and acquisition process. Many things can go wrong when a model is not carefully verified and validated. Not only does
lack of V&V make a model difficult, if not impossible, to use, but the model may fail to support its intended use. V&V
reduces the risks of developing an M&S that does not meet requirements or of using an inappropriate simulation to
support a decision. While risks can never be eliminated entirely, they can be quantified in a way that they provide the
decision maker with an indication of how high the cost of using an erroneous M&S result can be. This approach
therefore allows optimal decisions to be made. This paper gives a description of a methodology for implementing V&V
processes and documentation into the M&S design process.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
The problem of defending a specific airspace is among the main issues a military commander to solve. Proper protection
of own airspace is crucial for mission success at the battlefield. The military doctrines of most world armed forces
involve two main options of defending the airspace. One of them is utilizing formations of fighter aircraft, which is a
flexible choice. The second option is deploying modern SAM (Surface to Air Missile) systems, which is more expansive.
On the other hand the decision makers are to cope with miscellaneous restrictions such as the budgeting problems. This
study defines air defense concept according to modern air warfare doctrine. It considers an air defense scenario over an
arbitrary airspace and compares the performance and cost-effectiveness of employing fighter aircraft and SAM systems.
It also presents SWOT (Strenghts - Weakness - Opportunities - Threats) analyses of air defense by fighter aircraft and
by modern SAMs and tries to point out whichever option is better. We conclude that deploying SAMs has important
advantages over using fighter aircraft by means of interception capacity within a given time period and is cost-effective.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
Traditionally, military simulation has been problem domain specific. Executing an exercise currently requires multiple
simulation software providers to specialize, deploy, and configure their respective implementations, integrate the
collection of software to achieve a specific system behavior, and then execute for the purpose at hand. This approach
leads to rigid system integrations which require simulation expertise for each deployment due to changes in location,
hardware, and software. Our alternative is Software as a Service (SaaS) predicated on the virtualization of Night Vision
Electronic Sensors (NVESD) sensor simulations as an exemplary case. Management middleware elements layer self
provisioning, configuration, and integration services onto the virtualized sensors to present a system of services at run
time. Given an Infrastructure as a Service (IaaS) environment, enabled and managed system of simulations yields a
durable SaaS delivery without requiring user simulation expertise. Persistent SaaS simulations would provide on demand
availability to connected users, decrease integration costs and timelines, and benefit the domain community from
immediate deployment of lessons learned.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
The development of an Integrated Base Defense (IBD) is a significant challenge for the Army with many analytical
gaps. The IBD problem space is complex, with evolving requirements and a large stakeholder base. In order to
evaluate and analyze IBD decisions, the Training & Doctrine Command (TRADOC) Maneuver Support Center of
Excellence (MSCoE) led and continues to lead a series of IBD focused experiments and wargames. Modeling and
Simulation (M&S) significantly contributes to this effort. To improve IBD M&S capabilities, a collaborative
demonstration with the Research, Development and Engineering Command's (RDECOM's) M&S Decision Support
Environment (MSDSE) was held in September 2011. The results of this demonstration provided key input to MSCoE
IBD related concepts and technologies. Moreover, it established an initial M&S toolset that will significantly improve
force protection in combat zones and Army installations worldwide by providing leaders a capability to conduct
analysis of defense and mission rehearsals.
The demonstration was executed with a "human in the loop" Battle Captain, who was aided by mission command
assets such as Base Expeditionary Targeting and Surveillance Sensors-Combined (BETSS-C). The Common
Operating Picture was populated and stimulated using Science & Technology (S&T) M&S, allowing for a realistic
representation of physical phenomena without the need for real systems. Novel methods were used for simulation
orchestration, and for initializing the simulations and Opposing Force (OPFOR) activities. Ultimately, this
demonstration showed that the MSDSE is suitable to support TRADOC IBD analyses and that S&T M&S is ready to
be used in a demanding simulation environment.
This paper will highlight the event's outcomes and lessons identified.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
The amount of data processed annually over the Internet has crossed the zetabyte boundary, yet this Big Data
cannot be efficiently processed or stored using today's mobile devices. Parallel to this explosive growth in data, a
substantial increase in mobile compute-capability and the advances in cloud computing have brought the state-of-the-
art in mobile-cloud computing to an inflection point, where the right architecture may allow mobile devices to
run applications utilizing Big Data and intensive computing. In this paper, we propose the MObile Cloud-based
Hybrid Architecture (MOCHA), which formulates a solution to permit mobile-cloud computing applications such
as object recognition in the battlefield by introducing a mid-stage compute- and storage-layer, called the cloudlet.
MOCHA is built on the key observation that many mobile-cloud applications have the following characteristics:
1) they are compute-intensive, requiring the compute-power of a supercomputer, and 2) they use Big Data,
requiring a communications link to cloud-based database sources in near-real-time. In this paper, we describe
the operation of MOCHA in battlefield applications, by formulating the aforementioned mobile and cloudlet to
be housed within a soldier's vest and inside a military vehicle, respectively, and enabling access to the cloud
through high latency satellite links. We provide simulations using the traditional mobile-cloud approach as well
as utilizing MOCHA with a mid-stage cloudlet to quantify the utility of this architecture. We show that the
MOCHA platform for mobile-cloud computing promises a future for critical battlefield applications that access
Big Data, which is currently not possible using existing technology.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.