1. A Method for Determining Size and Burial Depth of Landmines Using Ground-Penetrating Radar (GPR) Jay A. Marble, Veridian, Ann Arbor, MI Andrew E. Yagle, University of Michigan

2. OVERVIEW OF TALK GOAL: Size and burial depth of landmines USING: Ground-Penetrating Radar (GPR) METHOD: Range-Migration Alg. (RMA) VALIDATION: 10 signatures of actual Russian TM-62M landmines (Army MHK) RESULTS: Consistent ability to determine: burial depth; diameter; height of landmines

3. Objectives of Algorithm Avoid false alarms (use up ceramic disks) Depth important (mines at most 6” deep) Size important (used ordnance strewn over) Metal detectors not enough; need more specific information about possible mines

4. Battlefield Vehicle Prototype Army Night Vision Electronic Science GPR, metal detector, infrared camera Robot arm will mark mine locations with ceramic disks (arm is not shown at right)

5. Ground-Penetrating Radar (GPR) Mine Hunter/Killer: Designed by BAE; $:Army Night Vision Lab (Fort Belvoir VA) 20 transmit/receive antenna pairs in front 256 frequencies; 500 Mhz to about 2 MHz; stepped by 5 MHz

6. Depth Processing of Data Continuous-wave stepped-frequency response Direct measurement of transfer function Sample every 2 inches in vehicle motion direction

7. Fourier Transform (FFT) Response(frequency) is r(f): Dwell time (one f)=0.15us; Penetration depth=7m (ε=9) Step size so no depth aliasing=1.1 MHz

8. Hyperbola: azimuth (along track) Buried point target located at (x0,z0). Antenna located along track at (x,0).

9. Significance of Hyperbola Avoids false alarms due to clutter and noise Stratified ground appears as straight line Hyperbola indicates real, localized target Hyperbola indicates its depth, as well

10. Range Migration Algorithm (RMA) Originally: Seismic imaging for oil domes “Migration” since images in raw data are “migrated” to their correct locations Later: adapted to SAR by Italians Frequency-domain migration: 1978 (Stolt)

11. Range Migration Equations D(kx,kz)=R(kx,w)=2-D space-time Fourier of r(x,t)

12. RANGE MIGRATION ALGORITHM: DIAGRAM

13. Experimental Validation: Data TM-62M anti-tank mine; buried 4”-8” 6” high=3 pixels@2” for 500 MHz-2 GHz Measured signature in Virginia clay (lossy) from MH/K above System calibration off

14. Experimental Validation: Result Image: top and bottom of mine (7” apart, 10” long) Shadow region between (radar can’t penetrate mine) Depth of top line=6”=correct depth of buried mine Need to estimate permittivity so flat top & bottom Thresholding for binary image makes image clearer

15. Experimental Validation: Result #med12345678910 Depth6.4 4.45.4 6.4 Width1620161220 161814 Height88988777878 10 signatures from same TM-62M mine using MH/K Fairly consistent (a few outliers); biased slightly high Unknown ground truth permittivity a likely problem: Different in free space, underground, in mine itself

16. Present Work on Landmines Issue: detection performance post-migration (easier to look for parallel straight lines) vs. detection performance w/pre-migration data (harder to look for hyperbolae, but apply to raw data before migration processing) Issue: how to look for lines or hyperbolae Issue: how to combine with other modalities

17. Determine size and depth of landmines using GPR as part of a multimodal detection algorithm Range Migration and phase compensation; Stoltz interpolation Successful detection of Russian mines buried in field from NVESD MH/K

18. RANGE MIGRATION ALGORITHM: EXPERIMENT Army NVESD MH/K USSR TM-62 LAND MINE Point-spread responseImaging a single point

19. RANGE MIGRATION ALGORITHM: RESULTS TM-62 measured (6” depth)TM-62 binary reconstructed