Automatic Target Recognition Using Passive Radar and a Coordinated Flight Model

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Automatic Target Recognition Using Passive Radar
and a Coordinated Flight Model

• Lisa M. Ehrman
• Advisor Aaron D. Lanterman

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What is ATR?

• Automatic Target Recognition (ATR)
• Ability to classify a target
• Two Schools of Thought
• Create images of the targets, which enable you to
  conduct ATR
• Conduct ATR directly on data, ie target RCS
• Our Approach
• Want to identify aircraft model
• Select Passive Radar as illuminator
• Use RCS to identify aircraft model

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What is Passive Radar?

• Active Radar
• System has transmitter and receiver
• Transmitter sends pulses which bounce off target
• Determine target position and velocity from
  energy that bounces back

• Passive Radar
• System only has a receiver
• System exploits transmitters already available,
• ie TV, FM Radio used to determine target
  position and velocity

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Why Use Passive Radar?

• Benefits
• Covert
• Cheap
• Not as susceptible to bad weather or stealth
• Lower frequencies ? RCS varies more slowly with
  time
• Challenges
• Transmitting signal not designed for target
  detection tracking
• Challenges have already been overcome by Howland,
  Herman, Lockheed Martin,

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Radar Cross Section (RCS)

• RCS Equation

• RCS Depends on
• Incident Azimuth and Elevation
• Observed Azimuth and Elevation

AZI
AZO
ELI
ELO
PD
PR
Transmitter
Receiver
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Coordinated Flight Model

• Goal
• Estimate Aircraft Orientation from Position
• Key Parameters
• Heading
• Pitch
• Roll
• Assume Yaw 0

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Modeling RCS

• 1) Use FISC to Model RCS as function of
• Incident Azimuth and Elevation
• Observed Azimuth and Elevation

2) Use NEC2 to Model Receiving Antenna Gain

• 3) Use AREPS to Model Propagation Losses
• Between Transmitter and Aircraft
• Between Aircraft and Receiver

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Creating Noisy Profiles

• Problem
• In Absence of Real Data, Simulate the Power
  Profile Arriving at the Receiver
• Add White Gaussian Noise
• Assume phase is equally likely everywhere in
  0,2p
• Traces out a circle in the Complex Plane, whose
  radius is the RCS magnitude
• Model the thermal noise as normally distributed
  white Gaussian noise, acting independently in the
  Real and Imaginary directions
• Add the noise to the profile using

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Computing Noise Power

• Noise Figure Vs. Noise Power

• Noise Figure Accounts for
• Out-of-Band Interference
• Direct-Path Interference
• Solution
• Sweep Noise Figure

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Identifying the Aircraft

• Use Loglikelihoods to Identify Aircraft Model
• Rician Model Compares the Library of Profiles to
  the Simulated Profile at the Receiver
• Treat each point in time as an independent sample
  of a process
• Loglikelihood is given by
• The aircraft with the largest loglikelihood is
  matched to the target

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Geometries Tested

• Simple Scenarios
• Straight and Level Flight
• Banked Turn
• Complex Scenario
• Real Flight Profile

The flight pattern is a F-15C trajectory,
obtained from the Joint Helmet Cuing system,
mission JH-16, conducted by the 445th Flight
Test Squadron at Edwards Air Force Base in May
2000.
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Straight and Level FlightProbability of Error
Vs. Noise Figure
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Straight and Level FlightPower Profiles
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Straight and Level FlightConfusion Matrices

• Noise Figure 35 dB, Noise Power -166 dB
• Noise Figure 40 dB, Noise Power -161 dB
• Noise Figure 45 dB, Noise Power -156 dB

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Banked-Turn Flight ProfileProbability of Error
Vs. Noise Figure
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Banked-Turn Flight ProfilePower Profiles
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Banked-Turn Flight ProfileConfusion Matrices

• Noise Figure 45 dB, Noise Power -156 dB
• Noise Figure 50 dB, Noise Power -151 dB
• Noise Figure 60 dB, Noise Power -141 dB

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F-15 Trajectory 3-D
Z
Y
X
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F-15 Trajectory Top View
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F-15 Trajectory, Real AnglesProbability of
Error Vs. Noise Figure
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F-15 Trajectory, Real AnglesPower Profiles
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F-15 Trajectory, Real AnglesConfusion Matrices

• Noise Figure 55 dB, Noise Power -146 dB
• Noise Figure 60 dB, Noise Power -141 dB
• Noise Figure 65 dB, Noise Power -136 dB

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F-15 Trajectory, Est. AnglesProbability of
Error Vs. Noise Figure
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F-15 Trajectory, Est. AnglesPower Profiles
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F-15 Trajectory, Est. AnglesConfusion Matrices

• Noise Figure 55 dB, Noise Power -146 dB
• Noise Figure 60 dB, Noise Power -141 dB
• Noise Figure 65 dB, Noise Power -136 dB

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Estimating Aircraft Heading
Z
Y
X
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Estimating Aircraft Pitch
Z
Y
X
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Estimating Aircraft Roll
Z
Y
X
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Conclusions

• Performance Varies Greatly with SNR
• If you can get SNR 1, this is a viable approach
• If you have trouble correctly identifying
  aircraft and SNR 1, you probably need a more
  sophisticated means for estimating aircraft
  orientation

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Future Work

• Finish the FISC Database, using more
  sophisticated techniques
• Determine whether or not the out-of-band and
  direct-path interference can be accounted for in
  this manner
• Determine impact of errors in position estimates

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BACK-UP SLIDES
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SYSTEM DESCRIPTION

• Transmitter
• GPS Location 520100 N, 050300 E
• Altitude (ASL) 375 m
• Frequency 100 MHz
• Peak Power 100 kW
• Type Omni-directional
• Polarization Horizontal
• Receiver
• GPS Location 520636 N, 041926 E
• Altitude (ASL) 100 m
• Direction 320 (0N, 90E, 180S, 270W)

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RECEIVER GAIN PATTERN