1. E limination of C lutter through S ignal P rocessing for L andmine / O rdnance D etection (ECSPLOD)  Gabriel Ford  Aniket Hirebet  Vasileios T. Nasis  Norman Butler  Advisor: Dr. Athina Petropulu May 29, 2002 Nic Dunlop

2. What are landmines?  Buried explosive devices.  Triggered by pressure or tripwire.  Types Anti-personnel Anti-tank  Cost 3 dollars to purchase.  Cost 1000 dollars to remove. Nic Dunlop

3. The Human Toll  Over 110 million mines are scattered across the world.  500 people are killed or injured every week by triggering landmines.  80% of the victims are civilians. Nic Dunlop

4. Why Metal Detectors Fail  Only effective when locating mines with substantial metal content.  Modern anti-personnel mines are made of plastics and contain dielectric explosives. National Defense Magazine

5. Ground Penetrating Radar (GPR)  Ground Penetrating Radar (GPR) can detect all types of landmines, including modern plastic mines.  Our project focuses on preprocessing to improve landmine detection. PreprocessingDetectionClassificationPreprocessing DeTec - EPFL

6. Experimental Setup  Ground Penetrating Radar (GPR) data was collected by DeTeC with a commercial SPRscan system.  Mines were buried in the center of a scanning pattern.  Each line in the scanning pattern represents a separate B-scan. DeTec - EPFL

7. GPR Data: A-scans and B-scans  A B-scan is a collection of A-scans recorded along a scanning line.  The vertical (time) axis corresponds to depth.  A B-scan represents a vertical slice of the ground. B-scan – Composed of A-scans  The received signal at any measurement point is called an A-scan. A-scan

8. The Problem: Signal Clutter  GPR images are marred by a high degree of clutter.  For homogeneous media, the clutter varies little over a B-scan.  As a result, the mine signal is still evident. PFM-1 Mine in SAND PFM-1 Mine in SOIL  For non-homogeneous media, the clutter is more random.  In this case, the mine signal is highly obscured. ?

9. Signal Clutter Defined  A-scan Model: w = c + b + s + e  The received signal w: c: antenna cross-talk b: ground bounce s: target signal e: measurement noise  Clutter is due primarily to ground bounce and antenna cross-talk. e s b c Tx Rx w c b

10. Clutter Reduction  Common clutter reduction methods include: subtracting a signal measured in the absence of a target subtracting a moving average estimate of the background ensemble mean subtraction  These procedures are ineffective for the general case of mines buried in non-homogeneous media.  We have developed ECSPLOD to specifically overcome this problem

11. Method of Solution  ECSPLOD extends mean subtraction with adaptive filtering for interference cancellation.  ECSPLOD updates the adaptive filter input signal to compensate for variation in clutter properties. x = n’ d = s+n d = s+n x = n’ Adaptive Filter SUM y - + e Mine Response

12. Raw DataMean Subtraction Plastic Mine in Sand – Mean Subtraction

13. Raw DataMean Subtraction Plastic Mine in Soil – Mean Subtraction

14. Plastic Mine in Soil: Moving Average Subtraction vs. ECSPLOD MAECSPLOD-KALMANECSPLOD-NLMS

15. Summary – ECSPLOD Raw DataMean SubtractionECSPLOD - NLMS

16. Plastic Mine in Soil – Detection Raw Data Moving Average SubtractionECSPLOD NLMSECSPLOD Kalman

17. Detection Evaluation – ROC Curves PFM - 1 in Soil, NLMSType 72 in Soil, NLMS

18. Economic Summary Out of pocket costs were under $500 (reference material and printing costs) Cost in private sector summarized below: Salaries$ 80,400.00 Fringe Benefits$ 11,656.80 Consulting Services$ 11,440.00 Hardware / Software / Equipment$ 7,608.00 Subtotal:$111,104.80 Overhead @ 100 %$111,104.80 TOTAL$222,209.60

19. Summary and Conclusions  The Problem: There is a need for a reliable demining technology Metal detectors do not work on all types of mines Ground Penetrating Data is suitable for all types of mines But GPR is plagued with the problem of excessive signal clutter

20. Summary and Conclusions  The Solution: Mean Subtraction only works in homogeneous media Moving Average Subtraction shows some improvement ECSPLOD utilizes Mean Subtraction followed by Adaptive Filtering ROCs and visual comparisons show that ECSPLOD works

21. Questions and Comments BeforeAfter ECSPLOD Special thanks to: Athina PetropuluWayne HillMaja BystromMoshe KamBrian Kravitz