Shared Synthetic Environment Risk Reduction Modeling and Simulation Re-Use

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Shared Synthetic EnvironmentRisk
ReductionModeling and SimulationRe-Use

• Dr. Gerald Prichard
• Jacobs Sverdrup / JSFPO MS TE
• 12-06-2006

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Wednesday, 6 December 1530 - 1700 Room W202
Special Event Sponsored by The Society for
Modeling and Simulation International MS Reuse
Success StoriesImproving Economics and
Effectiveness of MS Support to Warfighting
Moderator (5 Minutes) Dr Steve Flash
Gordon, Orlando Field Office Manager,
Georgia Tech Research Institute (GTRI)
Introductory Comments (10 Minutes) Current
Economics of MS Initiatives Mr. Bill
Waite, President, AEgis Technologies Group
Panelists (Up to 15 Minutes Each)
Virtual Environment Amphibious Assault
Vehicles (VEAAV) Turret Trainer Dr Denise
Nicholson, Senior Research Associate, Institute
of Simulation and Training, UCF Joint
Strike Fighter (JSF) Shared Synthetic Environment
Risk Reduction Activity Dr Gerald
Prichard, Deputy Mission Systems Test and
Evaluation, Joint Strike Fighter Program Office
Pioneer UAV Pilot Trainer Mr
Jeffrey Wallace, CEO/CTO, EnvoyTek, Inc
Future Combat System (FCS) MS Reuse Planning
Ms Phil Zimmerman and Mr Randy Ball,
Co-Directors MS Management, Program
Manager, Future Combat System Question and
Answer Session Approximately 15 Minutes to End
Special Session
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SSE Risk Reduction Activity Purposes

• Develop a Joint Strike Fighter-specific proof of
  concept RF and IR environmental simulation based
  on environmental concepts as specified in 2004,
  particularly for demonstration of RF and IR data
  correlation for both at-source and at-aperture
  values
• Acquire and integrate specific legacy, government
  models into the RF and IR environmental
  simulation
• Document the SSE Risk Reductions functional and
  design requirements, as well as the
  successes/limitations relative to a set of
  pre-coordinated technical metrics

The SSE Risk Reduction effort was a proof of
concept development conducted in 2004 to address
specific environmental and entity modeling
challenges and to test the viability of legacy
model re-use within such a development.
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Ground Based Laboratory Test Environment
F-35 Aircraft
Environment
Threat Target Entities
Multi-Ship F-35 Weapon System Simulations Include
Actual Aircraft Hardware/Software
Simulation Environment Generation, Execution
Control Provides A Virtual Combat Test Environment
Manned and Virtual Cooperative and Threat Weapon
System Simulations Employ Real Threat Tactics and
Capabilities
Visual Systems Provide Combat Realism
Knowledge External to a Simulated
Entity Processes to Manage and Communicate this
Knowledge Functions that Act and React on this
Knowledge and Databases that provide
cross-correlated representations
Integrated Air Defense Systems Provide Realistic
Threat Lay-downs
F-35 Cockpits Include Actual Aircraft Controls
and Displays
System Under Test
Environment Models
Entity Models
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SSE Risk Reduction Project Team
Project Manager Brad Sigley LM Aero Ft. Worth
Geographic Locations Fort Worth, TX Orlando,
FL El Segundo, CA Burlington, MA Baltimore,
MD Fredericksburg, VA San Diego, CA Huntsville,
AL Billerica, MA Nashua, NH
SSE Technical Lead Dr. Jennifer Deang
Task 2
Task 1
Task 1 Lead Bob Jeffers LM MFC
Task 2 Lead Gary Yokote NG El Segundo
Technical Lead Judy Bovankovich
LM STS Wayne Civinskas
Envoytek Jeff Wallace
Dynetics Cindy Griner
Aerodyne John Conant
NG-ES Baltimore Ted Drilling
JRM Technology Russ Moulton
NG El Segundo Gary Yokote
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Legacy Government Models

• Nine (9) sets of Legacy Government Models were
  acquired and integrated
• JSAF - Joint Semi-Automated Forces
• MODTRAN - MODerate spectral resolution
  atmospheric TRANSsmittance
• RADTRAN RADiated atmospheric TRANSsmittance
  algorithm
• SPIRITS - Spectral Infrared Imaging of Targets
  and Scenes
• MUSES - Multi-Service Electro-optic Signature
• XPatch - Far-field and near-field radar
  signatures for 3D target models
• Compact Terrain Data Base WGS-84 compliant
  terrain data base
• SPF, SPURC, SIIRM plume radiation models
• Gridded Weather Model

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Risk Reduction Software Reuse

• JSAF
• Aircraft
• Ground Radar Asset
• Tank
• Ownship

RF Display
IR Display
Radar Model
EO/IR Model

• Executive
• Model Initialization
• Enforce Runtime Rules
• Recording initialization

Simulation I/O

• API Function Libraries
• Access to SSE components

Test I/O

• SSE Broker
• Message Handling

• Legacy Models
• SPIRITS, MUSES
• XPATCH
• Terrex and Genesis
• Modtran, Radtran, et. al.

• SSE Control
• Timing Synch. Control

• Recorded Data
• Data Collection

• SSE Transaction Processes
• Provides data correlated _at_ aperture
• Utilizes SSE lower-level libraries/models
• Updates 3D geospatially databases

Analysis Tools
Offline Processing

• Common Environmental Data Representations
• Common Material-encoded Terrain
• Common Atmosphere
• Common Platform Models
• Common Material DB
• Common Aerosol DB
• Common Physical Property DB

• SSE Data Source Models
• Sensor Specific Pass-band Attenuation
• Signature Kinematics interpolation
• Clouds
• Line-of-Sight Utilities
• Coordinate Conversion Utilities
• Data Correlation (Spectral, Temporal, Spatial)
• Database store, update, retrieve processes

SSE I/O
Contains reused software
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Lessons Learned

• Government models require modifications beyond
  just a common API to meet sensor, entity, and
  environmental requirements
• Software licenses need to be clearly identified
  up front and managed
• Further architectural studies are required to
  address real-time requirements
• Management of a highly diverse, geographically
  separated team requires strong focus on
  system-level integration efforts
• Specification and coordination of technical
  success criteria is key to refining model
  development and focusing VV efforts
• Design of simulation architecture can mitigate
  data rights concerns

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SSE RR Model Re-Use Successes

• 1) Employed over 1 Million LOC with approx. only
  20 new code
• Re-used code
• JSAF entities (with interface changes)
• Government validated RF and IR
  environmental models (MODTRAN,
• RADTRAN, SPIRITS, MUSES, XPATCH, TEREX,
  COMPACT TERRAIN DB,
• SPF, SPURC, SIIRIM, Gridded Weather
  Model) ()
• () SSE RR environment was not embedded with
  sensors nor tied to entity representations
• New code developed for
• message handling
• time management/synchronization
• common RF and IR material encoding

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SSE RR Model Re-Use Successes (cont.)

• 2) Performed tasks over a 5-month period with a
  highly geographically distributed team at 10
  sites
• 3) Met 93 of all technical success criteria with
  focus on environmental correlations, including
  stressing entity movement and stressing clutter
  cases, environmental interactions, atmospherics,
  and weather
• 4) Demonstrated repeatable tests with all
  contractor and government-noted limitations
  documented

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SSE RR Model Re-Use Successes (cont.)

• 5) Incorporated time synchronization with
  multi-processor threading performed in a
  non-protocol specific manner in order to aid in
  meeting the timing-related success criteria
• 6) Insured that data rights for the government
  customer would be guaranteed via use of separate
  SW layer to perform correlations from
  environmental data sets (can separate analysis
  results from potentially proprietary data/models
  for data sources)
• 7) Demonstrated that legacy government models
  integration can be accomplished more broadly
  assuming architectural compliance for the entity
  model with the SSE RR interfaces.

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WORKING TO AFFORDABLY MEET THEREQUIREMENTS OF
THE WARFIGHTER
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• Back-ups

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SSE RR Technical Challenges relative to Model
Re-Use During Development

• 1) Entity model re-use challenges
• JSAFs interface implementation permitted JSAF to
  run as an external simulation with the SSE in a
  manner that is consistent with the SSE SSS, but
  not as accurately spatially and temporally as the
  internal-to-SSE implementation spectral
  metrics were not tested for the external-to-SSE
  implementation.
• JSAFs implementation for GCS cells relative to
  WGS-84 compliance would require additional
  development so that UTM coordinates for the CTDB
  would be able to match the GCS coordinates used
  for the MEDB.
• Hertz update rates of the SSE RRP were limited to
  integer divisors of 1000 since JSAF stores time
  in integer milliseconds.
• 2) Environmental source data/models re-use
  challenges
• The use of unclassified sources resulted in an
  inability to find solid models of the "targets"
  that did not already have a fixed number of
  facets,
• The number of facets could not be varied for RF
  signature calculations as needed to produce
  realistic, correlated signatures.
• ITAR restrictions prohibited access to highly
  validated data with more widely used air vehicle
  solid model for SPIRITS.
• Paint representations for the air vehicle
  target were different than those employed with
  the Physics Based Library in the past, Also,
  paints for RF signature calculations were
  different than those used for the EO/IR, but no
  negative impacts to metrics were noted.

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SSE RR Main Challenges relative to Model Re-Use
During Development (cont.)

• 3) Environmental model re-use challenges
• While no run-time requirements were part of the
  Risk Reduction Activity, the lack of modularity
  for the Physics Based Library caused significant
  run-time delays (approximately 2 times greater
  than real-time even with multiple processors)
• No RF shadowing effects were available with the
  Physics Based Library
• Variable-sized storage and weather cells and
  non-path-specific path layers for atmospheric
  attenuation were not available.
• Weather cells were rectilinear and uniform within
  cells, but discontinuous at cell boundaries.
  Origin and transformation of weather cell data
  from the Gridded Weather Model and its potential
  association with the Environmental Scenario
  Generator are unknown.
• 3D Clouds employed were not high resolution to
  permit reduction in visibility from natural sky
  cloud phenomena.
• 4) Synthetic imagery challenges
• SSE Image-like displays were generated from
  signatures and the Physics-Based Library provided
  actual BRDF from other models (X-patch, SPIRITS,
  MuSES).
• However, the number of at-source signature
  comparisons that could be performed were limited
  based on limitations for the MuSES model with
  respect to ability to generate at object
  signatures in an automated manner and its ability
  to employ refractivity for IR sources.
• 5) Model source code challenges
• The availability of model source code (including
  NDIAs as required) for development and for the
  VV agent.