Research & Development in Electromagnetic
Environment Effects (E³) Technologies
Application of AI/Expert Systems to E³ Modeling and Simulation—E³Expert
for Electromagnetic Compatibility (EMC) Modeling of Complex Systems
and Co-site Analysis of Multi-spectral (RF Communications and Radar) Systems/Environments
E³Expert, developed for the Air Force and Navy under
Small Business Innovation Research (SBIR) contract,
is ANDRO's premier AI/expert system based computer tool that is used to
predict intrasystem or co-site electromagnetic
interference/compatibility (EMI/C) for onboard systems (consisting of
antennas, wire cables, and equipments).It can also be used to analysis
intersystem or mutual electromagnetic coupling between external or
offboard sensor systems. The tool computes the electromagnetic coupling
between distributed aerospace, land, and marine systems deployed within
the RF battlespace volume. This involves
physical layer
modeling of reconfigurable
systems of systems
scenarios. At this layer, E³Expert models individual radars,
communications assets and information systems as nodes. The nodes are
then analyzed to compute mutual electromagnetic coupling interactions
as well as calculate the susceptibility/vulnerability response of the
nodes to cumulative incident energies from external sources. One of the
relevant E³ concerns is the effect of radar jamming sources on
communications systems and grids for assured RF communications,
information systems and network integrity, and tactical information
warfare.
Download the
E³Expert overview movie.
Development of Computational Electromagnetics (CEM) Software Toolkits—ICEMES
ANDRO's Intelligent Computational Electromagnetics Expert System (ICEMES),developed
for the Air Force under an SBIR contract, is used to produce valid
complex system CEM structure models given a set of
ensemble
problem drivers. An AI/expert system makes decisions based on
frequency, accuracy requirements, desired observables, etc. to provide
recommendations for optimizing the CEM model generation process from
the CAD data store to applying the appropriate physics, code and
solution method to ensure prediction accuracy.
System-Level Electromagnetic Phenomenology & Technologies to Bridge Component-Level to System-Level Analysis—EMMS
ANDRO's
Electromagnetic Modeling and Simulation System (EMMS),
developed for the Air Force under an
SBIR project, represents a new approach for accurately analyzing
complex electromagnetic systems by bridging the gap between
component-level and system-level electromagnetic phenomenology
understanding. A set of algorithms is used to model or characterize the
full range of electromagnetic behavior of canonical objects. These
algorithms are used to characterize the upper bound on the
electromagnetic behavior of simple canonical models in a generalized
way based on component-level measurement or high-quality synthetic
(simulated) data benchmarks (for antenna radiation, geodesic
coupling/isolation, intrasystem EMI/C, and scattering). The algorithms
can be used to extrapolate or interpolate component-level
electromagnetic effects to provide an accurate measure of system-level
electromagnetic responses and effects. The
EMMS concept is
used to demonstrate if system-level electromagnetic analyses of complex
systems are possible through the integration of component level
analysis techniques. A methodology has been generated for validating
the system-level electromagnetics analysis and to demonstrate
feasibility. This approach involves developing the scattering solution
of complex systems from simpler systems. In this manner, the
EMMS tool
can be used to validate existing electromagnetic simulation tools
that either solve the problem from first principles or are based on
approximate methods such as ray or geometric optics.
Development of Standards and Recommended Practices for CEM Modeling and Code Validation
ANDRO staff are
involved in the development of standards and recommended practices for
CEM modeling and code validation. This work is being conducted under
the P1597.1 IEEE Standard For Validation of CEM Computer Modeling and
Simulation and the P1597.2 IEEE Recommended Practice for CEM Computer
Modeling and Simulation Applications Working Groups, both sponsored by
the EMC Society Standards Development Committee.
Next-Generation Software Tools and Technologies
for Efficient RF Spectrum Management
Transmission Hypercube—Multiobjective Joint Optimization Technologies for Efficient Utilization of the RF Spectrum
ANDRO is developing and demonstrating
innovative concepts for spectrum management that enable the effective
and efficient joint utilization of all orthogonal electromagnetic
transmission resources, including, but not limited to, time, frequency,
geographic space, power control, modulation/code, beam direction and
polarization. This multi-dimensional environment is referred to as the
Transmission
Hypercube (TH), a term intended to convey the notion
of a multi-dimensional resource space (with n “degrees of
freedom”) in which each dimension allows orthogonality amongst users. This research
is aimed at developing approaches that consider the multi-dimensional
nature of the transmission space, the results of which are expected to
garner several orders of magnitude improvement in RF resource
utilization and therefore, aggregate information throughput. The
research is investigating the exploiting optimization and orthogonality
schemes that allow for multiple users while minimizing interference.
These include considerations for time slicing, frequency division
multiplexing, directional antenna arrays, spread spectrum codes, and
polarization. Joint optimization of the multiple orthogonalizing
transmission parameters can show that no two users are transmitting at
the same time, even though they may be using the same frequency in the
same space with the same exact spread spectrum code. Similar
illustrations can be given in the case of a spatially orthogonalized
system in terms of transmit beam patterns that do not overlap and
cross-polarized waves in ideal cases. The research is also exploiting
joint time-frequency transforms and waveform diversity technologies in
the context of software defined radio (SDR) operation. This work is
being performed under an SBIR contract for the Air Force and the Office
of the Secretary of Defense (OSD).
Ground-Based Computational TH Model Showing Spatial Beam Patterns
Radar Electromagnetic Scattering Analysis and Prediction
in Support of Automated Target Recognition (ATR) Technologies
and Sensor Applications
Bistatic, Monostatic and Multistatic Electromagnetic Scattering Modeling
Exploiting Waveform Diversity Technologies
Antenna Radiation Pattern Prediction
Autonomous Multi-sensor Registration Toolkits-SMART
Spatial Multi-sensor Autonomous Registration Toolkit
ANDRO's SMART is being
developed for the spatial alignment of multi-sensor and
multi-disciplinary images including synthetic aperture radar (SAR),
electro-optic (EO), infrared (IR), multi-spectral imagery (MSI),
signals intelligence (SIGINT) and ground moving target indicator (GMTI)
data collected from the battlespace. SMART provides a generic
concept of a geo-reference invariant feature that can be extracted from
each data source and generic algorithms for correlating salient
features across the multiple data sources and a fiducial database for
relative and absolute registration. Features that cross multiple source
data domains like radio/TV transmission towers, command and control
centers, road intersections, fixed search radar towers, and cellular
phone towers are considered. A reliable, flexible system that can tie
disparate types of sensor data together, provide tractable
error/uncertainty handling, and identify measures of effectiveness for
automatic convergence to minimize human intervention is being
developed. The selected algorithms are being implemented in a software
toolkit to enable the integration of different registration algorithms
for multi-source data. The focus in this R&D is on performing near
real time automatic geo-registration of multiple images from different
sensors in order to enhance the ability of military systems to identify
targets of opportunity with greater accuracy and confidence and to
support decision making for precision target geolocation applications.
Spatial Multi-sensor Autonomous Registration Toolkit (SMART) Concept
Information Fusion Architectures and Image
Analysis Tools for Enhanced Situational Awareness
ANDRO's
Information Fusion for Situational Awareness (InFuSA) System approach
provides a capability for aircrews and operators to efficiently handle
ever-increasing amounts and types of real time, near real time, and
non-real time information from on-board sensors, off-board platforms,
and other intelligent sources through effective fusion schemes. This is
for the purpose of determining target types and states with increased
confidence. To achieve this, the
InFuSA concept implements
a real-time multi-sensor data fusion system (MDFS) tree architecture
that integrates and registers data from multiple sensors, employs
knowledge-based decision algorithms to optimize information fusion
processes, computes target uncertainty using associated properties, and
supports the notion of a multi-modality human machine interface (HMI)
to enhance perceptual-cognitive threat target assessment. The sensor to
shooter cockpit warfighter, C2/C4I operator, or battlespace commander
can readily use this capability across various computing platfor ms
with little or no training to orchestrate defensive measures
(avoidance, ECM) or to eliminate hostile targets.
InFuSA
can provide the ability to fuse a broad range of information between
and across the C2ISR arena, and can expedite the development and
evaluation of fusion algorithms and data fusion automation technology.
ANDRO's
Integrated Target Image Expressed in a Common Operating Picture (iTimeCop)
Display concept addresses requirements for the development of
a new, cost-effective visualization system, which provides an
integrated picture of multi-disciplinary and multi-sensor (MD/MS) data
using a common display format, and which is adaptable to a variety of
display hardware. The development of an intuitive and straightforward
common display scheme permits single-type or fused sensor data to be
overlaid atop a digitized scene or view of the battlespace. Selected
MD/MS information/data sets are registered and integrated, and target
uncertainties are computed based on the pre-processed data to support
target identification tasks. This approach allows
iTimeCop
to be readily useable by a ground operator, battlespace commander, or
cockpit warfighter across various computing and display platforms. The
iTimeCop
capability represents an automated information
management and rapid decision-making tool.
Technologies in Support of Collaborative
and Concurrent Engineering Tasks
We make extensive use of robust software architectures and
generic, object-oriented data formats to facilitate portability and
extensibility of our tools. This is crucial for intelligently importing
and translating CAD or CEM structure models for use in the simulation
tools. Our expert system knowledge base modeling and data translation
tools are used to automatically read in and convert CAD or existing CEM
model data into our native
3-D metafile format. This format
provides a common database structure to represent modeling entities
(objects) in generalized form. These objects and their associated
attributes are stored in a metafile database internal to the system.
CAD formats currently supported are facet, DXF,
VRML , model
generated by
3-D Developer Studio (
3DS), and a
limited number of
Initial Graphical Exchange System
(
IGES)
entities. This database is shared with other
applications to perform various model validation, computational, and
reasoning tasks. In effect, this approach provides a means to support
collaborative and concurrent engineering tasks, and can be further
enhanced with the use of
eXtensible Markup Language
(
XML) technologies and techniques.
