A Weather Service for Introducing Dynamic Attenuation Factors in the Joint Integrated Mission Model

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A Weather Service for Introducing Dynamic
Attenuation Factors in the Joint Integrated
Mission Model
Dr. Michael A. Kelly, Shon D. Vick, John F.
Schloman, Frank A. Zawada Johns Hopkins
University/Applied Physics Lab michael.kelly_at_jhuap
l.edu
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Outline

• Impacts of the Environment in Battle
• Weather Server/Warfighter Model Integration
• Challenges of Transforming Weather to Weather
  Effects
• Rationale for Weather Effects Translater (WET)
• Concept and Approach
• Conclusions

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Dust Storm - OPERATION IRAQI FREEDOM

• Iraqis could not see through dust cloud
• The sensors on E8 JSTARS aircraft were able to
  identify ground targets despite near-zero
  visibilities caused by high dust concentrations
  in the atmosphere.
• The weather changed the outcome of a battle
  during OIF in March 23, 2003

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Weather Service/ DoD Model Integration
Environmental Service
Military System Model
Passive Sensors Active Sensors Weapons and
Countermeasures Systems/Platforms

• Observations
• Space
• Air
• Ocean
• Terrain
• Model
• GAIM
• MM5
• POM
• SIB II

• Effects
• Propagation
• Attenuation
• Heat/Cool
• Scintillation

• Impacts
• Obscurants
• Damage
• Traffic

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What Weather Observations Provide (Examples)

• Cloud Coverage
• Cloud Top Height
• Surface Visibility
• Surface Obstructions

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What Environmental Models Provide
Output from APL CARMA dust model

• Temperature
• Relative Humidity
• Cloud Water
• Dust Concentration

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What DoD System Models Require

• Employ sensor models to represent impact of the
  environment on combat
• Weather variables such as cloud water and dust
  concentration must be converted to quantities
  such as attenuation factor, propagation loss, and
  transmissivity
• Translation between environment and system
  effects differ among various models
• Develop a physics-based capability to translate
  fused weather data (reduce limiting assumptions,
  but retain high speed)

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Difficulty of Achieving Accurate Environmental
Representation

• Authoritative products require data
  verification, validation, and certification
  activities (Hummel and Blake 2001)
• Data produced with internally consistent
  procedure may still be inaccurate
• Environmental data can be authoritative, yet
  still provide incorrect conclusions in MS
  simulations
• Joint Live/Simulation
• Mission Rehearsals
• Post-mission Analysis

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Improved Environmental Technology

• Employs fuzzy logic as an objective technique for
  fusing diverse environmental datasets
• Provides more accurate four-dimensional
  representation of clouds and dust
• Ensures availability of environmental data over
  regions where observations are sparse

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Column Cloud Fraction
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Cross Section along 40.56ºN

• Allows cloud thickness for multiple layers to be
  determined from satellite imagery.
• Determined by fusing satellite data with model
  output

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Rationale for JIMM Weather Service

• Changing weather during a battle can be
  important, e.g. Dust storm during OIF
• Take advantage of new technologies in
  environmental analysis and modeling
• Reduce simplifying assumptions and
  parameterizations used to relate the environment
  and system impacts
• Develop a prototype for aircraft-tank engagements
  using IR sensors

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Joint Integrated Mission Model (JIMM)

• Primary modeling and simulation (MS) tool of the
  Joint Strike Fighter program
• Event-stepped, object-oriented model capable of
  simulating multiple-sided conflicts involving
  air, ground, naval, and space forces
• Simulates non-physical aspects such as tactics,
  organizational structure, attitudes, and
  contingency plans
• Represents physical aspects such as
  communications, physical disruption, movement,
  and the environment

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Signal-Loss Geometry
TL
Si
Ai di

• Represents weather effects on sensors and weapons
  systems through the use of attenuation factors,
  which quantifies extinction along the
  sensor-target line of sight (LOS).

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JIMM Weather Service
Adaptor
Weather FX Translator
JIMM
Modified Code
Raw Wx
SDB
TDB
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How It Works

• When a simulated event is about to occur, JIMM
  submits a request through the Adaptor to see if
  the opacity of the atmosphere has changed
• The request is transmitted to the WET, which
  interprets the request, performs the translation
  and any required interpolation/clustering
• The Adaptor constructs Shapes based on the
  attenuation factors received from the WET
• Based on the opacity of the atmosphere and the
  target-sensor line of sight, JIMM determines if
  the thermal contrast is sufficient for an
  aircraft to detect a hot tank

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Weather Effects Translator

• Employed MODTRAN and published studies to relate
  cloud water, aerosol concentration, and relative
  humidity to infrared absorption
• Translate the profile of temperature, relative
  humidity, cloud cover, cloud water, and dust
  concentration into attenuation factors
• Cluster the attenuation factors based on a
  K-means clustering algorithm
• Transmit the attenuation factors to the Adaptor,
  which constructs the shapes required by JIMM

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Modifications to JIMM

• Unaltered JIMM only allows shapes to be defined
  when scenario definitions are loaded at startup
• Shape definitions then remain static until
  completion of the run
• Codebase altered to allow creation and
  destruction of shapes on the fly
• Accomplished by modifying system requests for
  shapes to query the Adaptor for changes in the
  environment

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Notional Scenario

• Aircraft approach a tank from the NW, SW, NE, and
  SE.
• Cloud cover at different altitudes fed into the
  WET System
• Multiple simulations are performed with and
  without clouds

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Results

• Development was completed last week
• Analysis not yet complete
• Anticipate that the aircraft can detect the tank
  through clear skies and thin clouds
• Suggests that the direction of approach may be
  chosen to maximize the detection range

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Expected Impact of Weather in Single Engagement

• Shows impact of adding realistic weather on
  engagement
• Case 1 has no weather
• Case 2 has weather but no clouds
• Case three has weather and clouds

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Conclusions

• Focused on the representation of the natural
  environment in JIMM and its impact on a conflict
• Discussed the methods and software used to
  construct WET
• Described the modifications required for JIMM to
  accept inputs from WET
• Prototype weather service efficiently supplies
  weather data on demand