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Automatic Target Recognition Using Passive Radar and a ...

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Automatic Target Recognition Using Passive Radar and a ...

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    1. Automatic Target Recognition Using Passive Radar and a Coordinated Flight Model Lisa M. Ehrman Advisor: Aaron D. Lanterman

    3. 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

    4. 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,

    5. Radar Cross Section (RCS) RCS Equation:

    6. Coordinated Flight Model Goal Estimate Aircraft Orientation from Position Key Parameters Heading: Pitch: Roll: Assume Yaw = 0

    7. Modeling RCS 3) Use AREPS to Model Propagation Losses: Between Transmitter and Aircraft Between Aircraft and Receiver

    8. 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:

    9. Computing Noise Power Noise Figure Vs. Noise Power:

    10. 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

    11. Geometries Tested Simple Scenarios Straight and Level Flight Banked Turn Complex Scenario Real Flight Profile*

    12. Straight and Level Flight: Probability of Error Vs. Noise Figure

    13. Straight and Level Flight: Power Profiles

    14. Straight and Level Flight: Confusion 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

    15. Banked-Turn Flight Profile: Probability of Error Vs. Noise Figure

    16. Banked-Turn Flight Profile: Power Profiles

    17. Banked-Turn Flight Profile: Confusion 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

    18. F-15 Trajectory: 3-D

    19. F-15 Trajectory : Top View

    20. F-15 Trajectory, Real Angles: Probability of Error Vs. Noise Figure

    21. F-15 Trajectory, Real Angles: Power Profiles

    22. F-15 Trajectory, Real Angles: Confusion 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

    23. F-15 Trajectory, Est. Angles: Probability of Error Vs. Noise Figure

    24. F-15 Trajectory, Est. Angles: Power Profiles

    25. F-15 Trajectory, Est. Angles: Confusion 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

    26. Estimating Aircraft Heading

    27. Estimating Aircraft Pitch

    28. Estimating Aircraft Roll

    29. 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

    30. 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

    31. BACK-UP SLIDES

    32. 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 (0=N, 90=E, 180=S, 270=W)

    33. RECEIVER GAIN PATTERN

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