1 / 35

Advanced Imaging Approaches for Detecting Obscured Objects

Advanced Imaging Approaches for Detecting Obscured Objects . Sermsak Jaruwatanadilok Sumit Roy Yasuo Kuga Department of Electrical Engineering, University of Washington, Seattle, WA. BSI, Bellevue, WA, Feb 26, 2009. Overview. Goal and concepts Assets and capabilities

cathal
Télécharger la présentation

Advanced Imaging Approaches for Detecting Obscured Objects

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Advanced Imaging Approaches for Detecting Obscured Objects Sermsak Jaruwatanadilok Sumit Roy Yasuo Kuga Department of Electrical Engineering, University of Washington, Seattle, WA BSI, Bellevue, WA, Feb 26, 2009

  2. Overview • Goal and concepts • Assets and capabilities • Previous and on-going work

  3. Goal & Concepts GOAL: Improve detection and imaging of objects in obscuring and complex environments using electromagnetic waves Concepts: (1) Waveform design at transmitters to combat random media effects (2) Physics-based EM model of received signals (3) Signal processing at the receivers **Exploit relationship among (1), (2), and (3)**

  4. Assets and Capabilities • Analytical formulations • Angular / Frequency correlation functions of surface scattering • Two frequency mutual coherence functions of waves in random media • Numerical simulation tools • Monte Carlo simulations • Scattered waves in the presence of particle scatterings • Full-wave simulation tools • FDTD software • COMSOL Multi-physics • Experimental tools, equipments and facilities • Array imaging system • MMW systems • Anechoic chamber

  5. Current and Previous Work Related to BSI I. MMW active imaging of concealed objects II. MMW passive imaging of concealed objects III. Microwave imaging using angular/frequency correlation methods IV. Time reversal method and time reversal imaging V. Coherent array imaging VI. Focused pulse beam imaging VII. Detection of vehicle and human movement using existing communication systems Combined use of the physics-based EM modeling and signal processing

  6. I. MMW Active Imaging of Concealed Objects Simulated MMW Image Examples Optical image • Aperture radius = 30 cm • Distance = 1 m • Cloth material: cotton • Cloth thickness = 8 mm • Plastic explosive (C-4) 94 GHz simulated image 200 GHz simulated image

  7. Aperture radius = 30 cm Distance = 1 m Cloth material: cotton Cloth thickness = 1.2 mm Plastic explosive (C-4) Simulated MMW Image Examples Optical image 94 GHz simulated image 200 GHz simulated image

  8. ABCD matrix formulation Multi-layer Model

  9. Simulated MMW Pulse Imaging 94 GHz Aperture radius = 30 cm Distance = 1 m Cloth material: cotton Cloth thickness = 1.2 mm Plastic explosive object Bandwidth = 10 GHz 220 GHz

  10. II. MMW Passive Imaging of Concealed Objects [1] R. Appleby, (From previous slide) [2] National Academies, “Assessment of Millimeter-Wave and Terahertz Technology for Detection and Identification of Concealed Explosives and Weapons,” http://www.nap.edu/catalog/11826.html, 2007

  11. Simulated Passive Imaging Examples Optical image 94 GHz 220 GHz Cloth thickness = 1.2 mm OD = 0.123 OD = 0.288 OD = Optical depth Metal object OD = 0.826 OD = 1.9205 Cloth thickness = 8 mm

  12. III. Angular Correlation Function / Frequency Correlation (ACF / FCF) • Correlation of waves with different angles and frequencies • Exploit the difference of correlation characteristics when a target is presence compared to no target

  13. Experimental Studies of ACF/ FCF Memory Line • Strong correlation on ‘memory line’

  14. Use of Angular and Frequency Correlation Function (ACF/FCF) for Imaging • beam 1: 92 GHz – 96 GHz 10 degree • beam 2: 78 GHz 12 degree Equivalent to imaging but this shows presence of particle scattering Slope = 5.9 radians / GHz shrapnel Slope = 0.39 radians / GHz

  15. IV. Time-Reversal Method Concept of time-reversal imaging and focusing • Send probing signals • Obtain received signals (targets and surrounding) • To focus: re-transmit time-reversed signals To image: process time-reversed signals

  16. Time-Reversal Focusing Focusing improvement in random media (OD=optical depth) Geometry of the problem Snapshots of wave field in random media. (a) Gaussian pulse propagating through random media, (b) Time-reversed pulse back-propagated in the random medium. The energy focuses at the original source location.

  17. Time-Reversal Imaging • Multistatic data matrix • Time reversal matrix • How to model the time reversal matrix in the presence of random scattering media • Time reversal imaging • Time reversal MUSIC (multiple signal classification)

  18. Space-time transmitter-receiver 7-element array with half wavelength spacing is located at, and a point target is located at and in a random medium. The left figure shows array and image. Two figures on the right show images (in dB) in the dotted expanded area for OD = 0.1 and 0.5. Space-time time reverse MUSIC images in free space and random complex media at OD = 0.1 and 0.5. (dB scale) Figs. 5 and Fig. 6 show the result for identical physical problems. Note that space-time time reversal MUSIC has superior lateral resolution.

  19. V. Coherent Array (CA) Imaging and Detection of Object in Random Media (a) SAR images is formed using backscattering signals. Received signal is a response of a single transmitter (b) CA method coherently combines responses from all receivers and transmitters

  20. Numerical simulations: (a) SAR images (b) CA images CA method can mitigate effects from random scattering and clutter, but suffers the reduction in image resolution.

  21. VI. Focused Pulse Beam in Random Scattering Media • Effects from random scattering media on the imaging: two-frequency mutual coherence function • Contribution from target and media

  22. Focused Beam Imaging

  23. VII. Detection of Vehicles and Human Movement Using Existing Communication SystemsNewly Started Project in BSI

  24. Concept • Range-Doppler image using digital correlator • Angle-of-Arrival using MUSIC

  25. DETECTION SCHEME Adaptive Cancellation - Remove direct signal and clutter from surveillance channels to get true echo signal - Adaptive filter uses a lattice predictor structure

  26. Cross Correlation • Find Doppler shifts and time-delayed echoes of the targets. • Drawbacks: • Excessive processing time for long input signals • Decimation technique: discard data at Doppler frequencies we know targets do not exist before Fourier Transform

  27. D1 D3 D2 Time Delay  Range r1 + r2 = 2a b2 = a2-c2

  28. MUSIC Adaptive Beamforming to Get Angular Resolution

  29. Spatial Subarray Smoothing For correlated signals:

  30. Results from MUSIC AOA Estimation

  31. Some Simulation Results

  32. VIII. Array Imaging Systems • Range – angle imaging using step CW and angle of arrival processing

  33. MMW Radar for Imaging • Frequency 30 GHz (to be extended to 100 GHz) • Spotlight images using 2-D scan and stepped CW mode • Doppler images using 2-D scan and short pulse

  34. Spotlight image using 2-D scan and stepped CW mode Resolution Cross-range: ~ 2 degree (antenna beamwidth) Down-range: ~ 3 cm 5 GHz bandwidth Doppler images using 2-D scan and short pulse With a known vibrating source at 20 Hz (discrimination of an active source)

  35. On-going work • Improving modeling of wave propagation in random scattering media and clutters • Angular / Frequency correlation for detection and imaging of target • Ultra wide band time reversal imaging and focusing • Detection of vehicles and human movement using existing communication systems Future work • Collaborative imaging and detection from several receivers

More Related