Multiple High Resolution Simulations: Determining Unmanned Aerial Vehicle Vulnerability to Surfaceto

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Multiple High Resolution SimulationsDetermining
Unmanned Aerial Vehicle Vulnerability to
Surface-to-Air Engagements
Christopher A. Paganoni Systems Engineering Depar
tment (GMU)
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Objectives

• Purpose of the Simulation
• Overview of All Elements at Play
• Pre-Simulation Activities
• Simulation Activities
• Post-Simulation Activities
• Questions

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Purpose of the Integrated Simulation
Identify potential threats to Unmanned Aerial
Vehicles (UAVs) to Surface-to-Air Engagements for
the purpose of

• Mission Validation
• Mission Reconstruction
• UAV Vulnerability Assessment

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Models and Simulations in Play
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General Activities
The simulation system follows typical traditional
simulation processing steps

• Pre-Processing Activities
• Mission / Route Planning (Script Generation)
• Engagement Area Analysis (Graphical)
• Terrain Analysis (TTG / DTED Square Selection)
• Simulation Execution
• UAV 6-DoF Flight Simulation (60 Hz Sample Rate)
• ESAMS / RADGUNS / ALARM (1000 Hz Sample Rate)
• Post-Simulation Analysis
• 6-DoF Data Analysis (Both UAV and Interceptor)
• Engagement Analysis

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Pre-Simulation Activities
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N-PFPS (Encouraging Engagement)
N-PFPS (Personal Flight Planning Software)

• Detection Arcs
• Engagement Arcs
• Terrain Effects
• Multiple Threat Types
• Flight Path Analysis
• Multiple Terrain Map Types
• Route Overlay

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Sample Route With Detection Circle
Masking Effects due to Terrain and Placement of
ADS
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Sample Route with Engagement Circle
Masking Effects due to Terrain and Placement of
ADS
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Effects of Altitude on Detection(500 Ft AGL)
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Effects of Altitude on Detection(1000 ft AGL)
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Effects of Altitude on Detection(10,000 ft AGL)
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Simulation Execution
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Sample Sub-Systems Being Modeled(UAV 60 Hz
Collection Rate)

• Engine Model
• Control Surfaces
• Navigation
• Environment
• UAV Kinematics

• Radar Altimeter
• Kalman Filter
• CPU Registers
• C2

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Simulation Execution (A Little Detail)
Kalman Filters and Navigation

• Optimal recursive data processing algorithm
• Uses a combination of (1) system sensor
  dynamics, (2) statistical knowledge of the system
  sensors, and (3) any available initial
  information
• Provides a method of fusing these three types of
  information to compute an optimal estimate of the
  system state
  
• Good Resources for Kalman Filters
  http//www.cs.unc.edu/welch/kalman/Anchor-Rudolp
  h-6296
  
• For the Bold http//www.cs.unc.edu/welch/kalman
  /media/pdf/Kalman1960.pdf

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Simulation Execution (A Little Detail)
Using Inertial Navigation and GPS to Fuse
Guidance Information
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Sample Sub-Systems Being Modeled (Threat 1000 Hz
collection Rate)

• Flight Kinematics
• SNR for Tracking
• Track Conditions
• Environment
• Limited C2
• Monostatic (data)

• Bistatic (data)
• End Game Analysis
• PH (Prob of Hit)
• PK (Prob of Kill)
• Multiple Round Engagement

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Simulation Execution (A Little Detail)
Using RCS and the Radar Equation
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Simulation Execution (A Little Detail)
Using RCS and the Radar Equation

• S signal energy received by the radar
• Pavg average power transmitted by the radar
• G gain of the radar antenna
• radar cross section of the target
• Ae effective area of the radar antenna, or
  "aperture efficiency"
  
• tot time the radar antenna is pointed at the
  target (time on target)
  
• R range to the target

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Simulation Execution (A Little Detail)
Tracking the Target
A instantaneous position of the target
B instantaneous position of the illuminator
(constant) C instantaneous position of the seek
er a distance between the illuminator and the s
eeker b distance between the seeker and the tar
get c distance between the illuminator and the
target
Ttgt Independent Target Orientation
Yt-1 Northing Position from prior time step
Yt Northing Position from current time step
Xt-1 Easting Position from prior time step
Xt Easting Position from current time step
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Simulation Execution (A Little Detail)
Engaging The Target
Observation Angle
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Running the Simulations in Tandem
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Simulation Execution (Flow)
Combination of Time Driven and Event Driven
Execution
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Endgame Analysis

• Proximity Fuzing Fuzing criteria cause warhead
  to detonate
  
• Contact Fuzing Fuzing occurs as a result of
  physical contact
  
• Blast Kill Methodology Kill based on explosive
  force of interceptor warhead
  
• Fragmentation Kill Methodology Kill based on
  fragment penetration using vulnerability maps
  

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Proximity Fuzing for Endgame Algorithm

• The glitter points for the target are calculated
  in the inertial reference frame for the target
  relative to the targets center of gravity.
  
• All glitter points are tested one-by-one until
  either fuzing occurs, or all points are tested
  without result. This is done in the following
  fashion
• Glitter points are transformed into the inertial
  reference system.
  
• The vector is then added to the center of
  gravity.
  
• The vector from the interceptor to the glitter
  point is then calculated.
  
• Next the look angle from the interceptor roll
  axis is calculated
  

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Proximity Fuzing for Endgame Algorithm(cont.)

• In order to fuse, there are two criteria that
  must be met
  
• The glitter point must be located within the
  prescribed fuze cone, and
  
• The target must be within the specified fuze
  range.
  
• If the fuze is represented by active radar fuze
  power, the radar range equation and RCS of the
  target are used. The power seen by the fuze is
  then compared to the power level required. When
  the fuzing criteria are met, the warhead
  detonates after a time delay.

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Post-Simulation Products
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Output Products Usage

• Vehicle Engagement Potential
• Endgame Analysis (Pk)
• Vehicle Flight Path Projection
• Interceptor Flight Path Projection

• Mission Validation
• System Validation
• Mission Survivability
• Mission Reconstruction

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What the Simulations do Well

• UAV simulation is accredited by the system
  community.
  
• Verified by Telemetry vs. Simulated tracks
• Monitored operational flight
• Threat systems provide very reasonable detection,
  tracking, and engagement solutions based on the
  systems employed.
  
• Threat systems can be used in networked
  configurations allowing C3 simulation and
  engagement hand-off.
  
• Individual threat batteries can perform salvo or
  shoot-look-shoot scenarios.
  
• Interceptor Fly-Out and guidance is very
  accurate (accredited).
  

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Where are the Challenges?

• Mismatched Terrain Models (Ramping strategies)
• Out of synchronization for internal clocks of
  simulation (60 Hz vs. 100 Hz)
  
• Models use different memory approaches (Little
  Endian vs. Big Endian)
  
• UAV Simulation uses true geodetic coordinates
  while the intercept models use X-Y coordinates.
  
• The intercept models use local reference frames
  in respect to launch point, while the UAV uses a
  reference frame in respect to the vehicle
  position.
• End game analysis statistics are misleading in
  terms of true Pk or Pf the statistics tend to
  converge to a constant percentage.
  

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Questions?
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Back-up Material
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A Quick Definition
A 6 degree of freedom (6-DoF) simulation is in
respect to the 6 possible motions of an aircraft

• Heave
• Roll
• Pitch
• Yaw
• Longitudinal Motion
• Lateral Motion

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ALARM
Advance Low Altitude Radar Model
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ESAMS
Enhanced Surface-to-Air Missile Simulation
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RADGUNS
Radar-Directed Gun System Simulation
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Threat Template
 
  AUNCLASSIFIED B China Lake Area B B Site 1
C NZONE_OF_INF 24000.0 NANGULAR_RES 5.0000
NREF_INDEX 1.0000000 NX_RESOLUTION 500.0 NY_R
ESOLUTION 500.0 NLATITUDE 343845000N NLONGITU
DE 1200501000W NANT_HEIGHT 4.7 NFREQ_BAND XBF
NRADAR_FREQ 12200000000 NPULSE_WIDTH 0.0088
NBEAM_WIDTH 1.1 NRANDOM_SEED 123456 NMEAN_SWIT
CH 2 NIUZTER 1 NSIGMA_CONST 0.0003 ZUNCLASS
IFIED  
 
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References
Survivability / Vulnerability Information
Analysis Center
http//www.surviac.com
N-PFPS 3.1.2 SSC SD C4I Programs Office, Philadel
phia 700 Robbins Avenue, Building 2A Philadelphi
a, PA 19111 Attn N-PFPS Support Coordinator 1-
888-826-7748 N-pfps_at_spawar.navy.mil
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References (cont.)
Maybeck, Peter S. Stochastic Models , Estimation,
and Control (Vol. 1), Academic Press, New York,
NY (1979) Radar Cross Section References http//
www.aerospaceweb.org/question/electronics/q0168.sh
tml