19 April 2004

1
19 April 2004
Synthetic Environment Integrated Testbed
Infrared Intelligence, Surveillance, and
Reconnaissance Thread (IR ISR)
Kevin Dennen Dr. Will Clayton ERC,
Incorporated Tim Clardy Redstone Technical Test
Center
2
OverView

• Purpose
• Operational Overview
• Progression
• Models Terrain and Targets
• Synthetic Imagery
• Future Planning
• Teaming Efforts With NVL
• DTE 4 Planning Details
• Summary

3
SEIT IR ISR THREAD

• PURPOSE
• Operational Representation Of IR Sensor Fields Of
  View (Platform Perspective)
• Detect, Recognize, Identify And Locate Red
  Threats On Simulated Battlefield
• Provide Information On Red Forces To Populate
  SPOT Reports
• Test IR Sensor Performance Utilizing Test
  Instrumentation
• Sensor To Shooter Interface
• Conduct Battlefield Damage Assessment (BDA) Of
  Enemy Forces

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SEIT IR ISROPERATIONAL OVERVIEW
Red Forces
Operational Scenario Generation
Information
Information
OTB
Distributed Test Control Center (DTCC)
Blue Forces
IR Sensor Scene Generation
EPG STORM / RPWS SPOT Reports
B3
B4
HPC
B2
B5
DEGA
HPC
HPC
Sensor
IR Battlefield Imagery
RPWS Battlefield Map
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SEIT IR ISR CREW STATIONS
IR Sensor output
Terminal to HPC computer creating IR Scene
IR sensor detecting IR energy from scene
projection test hardware
Joystick used to pan battlefield, locate red
targets, and initiate laser range finder
STORM RPWS station for SPOT report generation
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SEIT IR ISR PROGRESSION
Capability
Increase in Synthetic Representation
Capabilities In IOCs are Cumulative and Building
Upon One Another
Time
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SEIT Terrain And Targets

• Terrain was created by Yuma Proving Grounds
  Digital Terrain Group
• Targets came from various sources
• Signature Research Predictive Models
• RTTC Coreset Empirical Models
• Other Test Centers Visible Models Converted to
  Infrared

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YPG Synthetic Infrared Terrain
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Infrared Vehicle Examples
M113 Model from Signature Research Inc.
BMP2 Model From RTTC Coreset Targets
Both Targets are Measured/Modeled for YPG Summer
Day
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IR Sensor Capabilites

• Pan Battlefied Using BG Flybox
• Ability To Turn Sensor Effects On/Off
• WFOV/NFOV
• DIS Entity Information
• Simulated Range Finder
• Automated Spot Reports of Enemy Vehicles Sent to
  RPWS

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Scenes From SEIT
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FCS LSI SDD IPP 1PLATFORMS SENSORCAPABILITIES

• Manned Ground Vehicles
• Infantry Carrier Vehicle (ICV)
• Mounted Combat System (MCS)
• NLOS-Cannon (NLOS-C)
• NLOS Mortar (NLOS-M)
• Recon Surveillance Vehicle (RSV)
• Command Control Vehicle (C2V)
• Medical Vehicle Extraction (MV-E)

• Unmanned Vehicles
• Multifunction Utility Logistics
• Equipment Vehicle Transport
• (MULE-T)
• MULE Assault (Light) (ARV-A (L))
• MULE Counter Mine (MULE-CM)
• Small Unmanned Ground Vehicle
• (SUGV)
• UAV Class I IV

• Sensor Capabilities (Multiple Systems)
• Detect Targets With IR Sensor
• Conduct BDA in EO Stare Mode
• Conduct BDA with Short Range EO
• Sensor
• Conduct BDA with Medium Range EO
• Sensor

• Unattended Munitions Sensors
• NLOS Launch System (NLOS-LS)
• Intelligent Munitions System (IMS)
• Unattended Ground Sensors (UGS)

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Future Efforts

• Exploring Possible Teaming Effort With NVESD
• Increase Fidelity For Synthetic Environment
  Representation
• Additional SEIT Viewing portal in Washington, DC
• NVESD has developed a simulation toolset to
  support the development, integration, test, and
  evaluation of FCS networked sensors (UGS, UAVs,
  UGVs) and Intelligent Munition Systems (IMS)
  that provides
• Simulation of Acoustic/Seismic Unattended Ground
  Sensors with and without EO/IR Imagers
• Simulation of Intelligent Munition Systems (IMS),
  Mines and Countermine Equipment
• Simulation of EO/IR Sensors on UAVs, UGVs, and
  RSV platforms
• Operator interfaces allowing crew interaction

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FCS 2-MAN RECONNAISSANCE AND SURVEILLANCE
VEHICLE (RSV) SIMULATOR
Driver DVO and IR views (Long Wave Uncooled)
Universal Controller UGS/IMS, UAV, UGV Control
Station
Scout IR views (2nd Gen FLIR, WAS, AiTD)
Driver station
Joy Stick controls
Hardware shown is based on UAMBLs Advanced
Concept Research Tool (ACRT)
SC4/MC2 SA display
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NVL COMPREHENSIVE MINE AND SENSOR SERVER (CMS2)

• Discrete, high res simulator for mines,
  unattended ground sensors and Intelligent
  munition systems
• Operates in conjunction with force-on-force
  simulation engines (OneSAF Testbed )
• Allows large scale simulation of mines or
  distributed sensors with minimal network burden
• Physics-based sensor models
• NVESD Acquire IR search and target acquisition
  model
• ARL Acoustic Battlefield Aid
• ERDC CRREL Seismic Sensor Performance Evaluation
  Model

Acoustic Pd footprint from ABFA
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NVL PORTAL CAPABILITY

• Viewing For Local Washington DC Personnel
• 135 X 65 Foot Projection System Tied To DREN
• Real Time Video Mixing Allows Up To 16 Different
  Views Of Exercise To Be Presented At Once
• Can Be Used In Classified Or Unclassified Mode
• Used For The 1st APP Showing
• Formal LSI SoSIL Facility
• Can Be Tied Into The WSMR IRCC As A Viewer

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SEIT DTE 4 CAPABILITIES PLAN

• Reconnaissance and Surveillance Vehicle (RSV)
• Scout and driver stations
• Mast mounted TA/ISR sensor suite
• UAV, UGV, and/or UGS/IMS controllers
• Implement three RTTC, NVL, and Fort Knox Battle
  Lab
• Command and Control Vehicle (C2V)
• 5 Scout work stations with automated spot report
  into Role Player Work Station (RPWS)
• Similar to IOC3 implementation
• Live range vehicle interface (UAV, T72, TBD)
• Map RTTC TA3 to area in Caspian Sea database
• NVL Portal viewing for local Washington DC
  attendance

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RTTC DTE4 C2V STATION ENHANCEMENTS

• Technology Transition To PC-based Scene
  Generator
• Overcomes 6 Platform Limit Due To Scarce HPC
  Resources
• Increases Portability Of Scene Generators
• Reduced Operational Cost
• Allows Operators The Ability To Quickly Switch
  Between
• Visible And IR Views
• Increased Fidelity And Performance Of Sensor
  Parameters
• Due To PC GPUs
• Provide Displays For Both Driver And RSTA
  Sensor
• Leverage NVESD FCS Simulations Where Applicable

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SUMMARY

• SEIT IR ISR Represents The Soldiers Eyes In
  The Battlefield
• IR ISR Synthetic Representation Is Advancing At
  Every Opportunity
• Teaming Arrangements with External Organizations,
  such as NVL, and Leveraging Of Capabilities Are
  Being Actively Pursued
• Integration with Live Assets And Test Ranges Are
  Increasing