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Humanitarian Demining with Ultra Wide Band Ground Penetrating Radar

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  • Current humanitarian demining rate is low and expensive. Therefore a global effort must be done worlwide to fight this issue. The overall political and legal framework is covered by the Ottawa Treaty from December 1997
  • GPR can work either in time domain or frequency domain
  • Response signal sn(t), ground reflection bn(t) and random noise e . It is usually expressed in Volts in the time domain
  • At the present time, no one standing-alone sensor or demining technique has shown total reliability in all sorts of environments and conditions. This leads to the idea of combination of several types of sensors to improve single performance.
  • Ground Bounce Removal, Clutter reduction, Soil effects filtering, Background mitigation, Background subtraction.
  • Landmines signatures must be extracted from raw data.
  • Data Focusing, Imaging or Migration
  • equally distributed weights assures acceptable performance in all sorts of scenarios. Such an approach is followed
  • Best results are shown. A study of parameters have been done for each algorithm
  • ALPHA=0.3
  • being N the number of A-scans involved in one single background calculation
  • The targets are isolated scatterers, or the distance among them is large; Constant roughness or smoothly varying background along the track under survey.
  • The targets are isolated scatterers, or the distance among them is large; Constant roughness or smoothly varying background along the track under survey.
  • The weight Wn ( ti ) applied to the ith data sample of the nth A-scan is computed as the ratio of the total instantaneous amplitude within the averaging window over the instantaneous amplitude associated with the data sample An(ti).
  • Main objective in this technique is tracking of the surface profile by subtracting a modified version of a preselected A-scan.
  • Main objective in this technique is tracking of the surface profile by subtracting a modified version of a preselected A-scan.
  • The signal in the local area minimizing the up most equation for component An(ωk) is the Reference Background for such a frequency component.
  • The signal in the local area minimizing the up most equation for component An(ωk) is the Reference Background for such a frequency component.
  • Operations are done in the original time-domain; Signals involved in calculations are not Complex (as in frequency domain) but Real; Optimization of parameters αn,i and ζn,i has to be done only once for each A-scan under process (instead of K as before).
  • It is a two-dimensional approach to a Moving Average subtraction. Averaging is made within a circular local area centered in the A-scan under process. Spatial window is that of a cylinder whose basis is surrounding the A-scan to be processed and thus corresponds to the geometry of cylindrical landmines.
  • In the particular situation when a GPR array is used, averaging window becomes an ellipse due to different resolution in along-scan ( dx ) and cross-scan ( dy ) directions. α and β define the ellipse. In the latter case, different time delays of back-scattered waves reaching each receive antenna have to be taken into account and thus compensated.
  • In the particular situation when a GPR array is used, averaging window becomes an ellipse due to different resolution in along-scan ( dx ) and cross-scan ( dy ) directions. α and β define the ellipse. In the latter case, different time delays of back-scattered waves reaching each receive antenna have to be taken into account and thus compensated.
  • Those 3 may be suitable to be included in the processing chain of the self developed IRCTR GPR system
  • Those 3 may be suitable to be included in the processing chain of the self developed IRCTR GPR system
  • Those 3 may be suitable to be included in the processing chain of the self developed IRCTR GPR system
  • Those 3 may be suitable to be included in the processing chain of the self developed IRCTR GPR system
  • At the present time, no one standing-alone sensor or demining technique has shown total reliability in all sorts of environments and conditions. This leads to the idea of combination of several types of sensors to improve single performance.
  • At the present time, no one standing-alone sensor or demining technique has shown total reliability in all sorts of environments and conditions. This leads to the idea of combination of several types of sensors to improve single performance.
  • At the present time, no one standing-alone sensor or demining technique has shown total reliability in all sorts of environments and conditions. This leads to the idea of combination of several types of sensors to improve single performance.
  • At the present time, no one standing-alone sensor or demining technique has shown total reliability in all sorts of environments and conditions. This leads to the idea of combination of several types of sensors to improve single performance.
  • At the present time, no one standing-alone sensor or demining technique has shown total reliability in all sorts of environments and conditions. This leads to the idea of combination of several types of sensors to improve single performance.
  • At the present time, no one standing-alone sensor or demining technique has shown total reliability in all sorts of environments and conditions. This leads to the idea of combination of several types of sensors to improve single performance.
  • At the present time, no one standing-alone sensor or demining technique has shown total reliability in all sorts of environments and conditions. This leads to the idea of combination of several types of sensors to improve single performance.

Transcript

  • 1. Background Removal in Array-Based UWB Radars for Landmine Detection Delft University of Technology, The Netherlands Public University of Navarre, Spain Álvaro Muñoz Mayordomo Dr. Miguel Ángel Gómez Laso Dr. Alexander G. Yarovoy
  • 2. CONTENTS
    • INTRODUCTION: The Landmine Trouble Worldwide
    • GROUND PENETRATING RADAR IN HUMANITARIAN DEMINING
    • SCOPE OF THIS THESIS: Clutter Removal
    • LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • METHODS COMPARISON
    • INFLUENCE OF TECHNIQUES ON LANDMINE DETECTION
    • CONCLUSIONS AND FUTURE WORK
  • 3. Background Removal in Array-Based UWB Radars for Landmine Detection
    • INTRODUCTION: The Landmine Trouble Worl dwide
    INTRODUCTION
  • 4. INTRODUCTION: The Landmine Trouble Worldwide
    • Foremost side effect after wartime  Forgotten landmines
    • At least 60 million undetected terrestrial landmines spread over countries in every continent
    • 70 people injured every day (26000 victims a year)
    • 90% civilian population
    • Major problem in agricultural-based regions.
    • Cause of displacement
    • Obstacle to reconstruction after hostilities
    INTRODUCTION
  • 5. INTRODUCTION: The Landmine Trouble Worldwide
    • Humanitarian Demining  Restoring land to the population
    • Current –manual– humanitarian demining rate ~ 100 thousand/year
    • Cost of removing a single landmine  100-300 times higher than production cost.
    • Removing 5000 landmines = one dead person and two injured.
    • Sanitary expenses = 10 hundred thousand euros per year
    INTRODUCTION
  • 6. INTRODUCTION: The Landmine Trouble Worldwide
    • Traditional
    • Demining Techniques
    • Prodders
    • Metal Detectors
    INTRODUCTION
  • 7. INTRODUCTION: The Landmine Trouble Worldwide
    • Traditional Demining Techniques
    • Mine-Detection dogs
    • Ground-engaging machines
      • Flails
      • Rollers
      • Millers and Tillers
      • Sifters
      • Dozers and graders
    INTRODUCTION
  • 8. INTRODUCTION: The Landmine Trouble Worldwide
    • Innovative Demining Techniques
    • Chemical sensing
    • Infrared imaging
    • Biosensing and explosive particle detection
    • Nuclear and atomic methods
    • Passive millimeter wave sensors
    • Acoustic impulses
    • Ground Penetrating Radar
    INTRODUCTION
  • 9. Background Removal in Array-Based UWB Radars for Landmine Detection
    • GPR IN HUMANITARIAN DEMINING
  • 10. GPR IN HUMANITARIAN DEMINING
    • Basic principles
      • Time domain or impulse GPR
        • Discrete pulses of nanosecond duration
        • Digitizes  GHz sample rates
      • Frequency domain GPR
        • Series of frequency steps
        • Chirp
        • Conversion  time domain
    INTRODUCTION GPR
  • 11. GPR IN HUMANITARIAN DEMINING
    • Basic principles
    • Majority of today's GPR technology based on Impulse Radar
    • Single echo return at a position n  A-scan
    • Recording time  Depth range
    • Expressed in Volts
    INTRODUCTION GPR Antenna Crosstalk Ground Bounce Target Response Antenna Crosstalk
  • 12. GPR IN HUMANITARIAN DEMINING
    • Basic principles
    • Whole ensemble of A-scans  B-scan
      • 2D subsurface Propagation time
      • picture Along-scan Position
      • 3D subsurface Propagation time
      • picture Along-scan Position
      • Signal Amplitude
    INTRODUCTION GPR
  • 13. GPR IN HUMANITARIAN DEMINING
    • Basic principles
    RAW DATA DATA AFTER SUBTRACTION INTRODUCTION GPR
  • 14. GPR IN HUMANITARIAN DEMINING
    • Basic principles
    DATA AFTER SUBTRACTION DATA AFTER FOCUSING INTRODUCTION GPR
  • 15. GPR IN HUMANITARIAN DEMINING
    • IRCTR UWB Mini-Array GPR
    • Global Project named CADMIUM
    • IRCTR-TNO collaboration
    • New terrestrial vehicle for landmine detection
    • Multisensor
      • Metal detector
      • Infrared sensor
      • GPS system
      • UWB GPR   
    INTRODUCTION GPR
  • 16. GPR IN HUMANITARIAN DEMINING
    • IRCTR UWB Mini-Array GPR
    • Main novelty  Modular approach
      • Independent modules
      • Reduction of electronics and number of antennas
    • Pulse generator 500 kHz
    • Connected to both TX antenna and RX array
    INTRODUCTION GPR
  • 17. GPR IN HUMANITARIAN DEMINING
    • IRCTR UWB Mini-Array GPR
    • Choice of waveform  Major role in GPR detection
    • Goals
      • Penetration depth: Freqs<1GHz
      • Resolution several cm: large bandwith  3GHZ
      • Low early and late ringing
    INTRODUCTION GPR
  • 18. Background Removal in Array-Based UWB Radars for Landmine Detection
    • SCOPE OF THIS THESIS: Clutter Removal
    INTRODUCTION GPR Clutter Removal
  • 19. SCOPE OF THIS THESIS : Clutter Removal
    • Ground Bounce and Antenna Effects Mitigation
    Antenna Crosstalk Ground Bounce Target Response Ground Bounce Target Response Antenna Crosstalk Antenna Crosstalk INTRODUCTION GPR Clutter Removal
  • 20. SCOPE OF THIS THESIS : Clutter Removal
    • Dedicated processing  Extract the target signal
    • Deeply buried landmines
    • Landmine is shallowly buried or laid on the ground
      • Target signal and surface signal are close and overlap
    • Landmine is small or dielectric-made
      • Scattering strength is lower
    INTRODUCTION GPR Clutter Removal
  • 21. SCOPE OF THIS THESIS : Clutter Removal
    • Background Subtraction  Topic of this thesis
    • Radar processing chain  BG removal precedes Focusing
    • Always error while estimating the BG  Residues
    • Level of residues depends on particular BG estimation
    • Objectives and approach
      • Implementation of techniques
      • Evaluation before Focusing
      • Selection Online algorithms
            • Offline algorithms
      • Evaluation after Focusing
    INTRODUCTION GPR Clutter Removal
  • 22. SCOPE OF THIS THESIS : Clutter Removal INTRODUCTION GPR Clutter Removal LITERATURE SURVEY ALGORITHM IMPLEMENTATION ALGORITHM TESTING ONLINE APPROACH OFFLINE APPROACH PERFORMANCE STUDY SCENARIO A SCENARIO B SCENARIO C SCENARIO D Signal-Background Ratio Comput. Requirements Signal-Background Ratio Comput. Requirements EVALUATION AFTER MIGRATION SCENARIO E Energy-Background Ratio SCENARIO C SCENARIO D
  • 23. Background Removal in Array-Based UWB Radars for Landmine Detection
    • LITERATURE OVERV IEW AND ANALYSIS OF TEC HNIQUES
    INTRODUCTION GPR Clutter Removal ANALYSIS
  • 24. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • Description of Test Scenarios
    INTRODUCTION GPR Clutter Removal ANALYSIS Plastic mines, 12cm Semi-buried and 5cm 6 Rough with grass E Plastic mine 13cm; Plastic mine 8cm; one rock; one screw 5cm 4 Very rough D Metal/Plastic/Cylinder, 10cm 3 Plastic cylinders, 5.4cm 2 Plastic mines, 13cm 5cm 8 Quite flat C Metal/Plastic cylinders and pipe 5-10cm Surface 7 Flat B Metal disk, 10cm Surface 1 Flat A Type of targets Depth Number of Targets Roughness Scenario features Data set
  • 25. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • 1) High Pass Filter
    • 2) Exponential Averaging
    • 3) Linear Prediction
    • 4) Moving Average
    • 5) Moving Median
    • 6) Weighted Moving Average
    • 7) Cylindrical Moving Average
    • Shifted and Scaled Background
      • Arbitrary Reference BG
      • Frequency Domain
      • Time Domain
    • 9) Principal Component Analysis
    INTRODUCTION GPR Clutter Removal ANALYSIS
  • 26.
    • FIR High Pass Filter
      • Two contiguous A-scans in background calculation
      • Equally distributed weights
      • High speed
      • Little memory usage
    LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES S. Nagwa, M. Bames, “A moving target detection filter for an ultra-wideband radar” Scan Direction INTRODUCTION GPR Clutter Removal ANALYSIS dx dy 0.5 A n (t) A n-1 (t) b n (t)
  • 27. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • FIR High Pass Filter
    Scenario A RAW DATA DATA AFTER SUBTRACTION INTRODUCTION GPR Clutter Removal ANALYSIS
  • 28. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • FIR High Pass Filter
    Scenario B RAW DATA DATA AFTER SUBTRACTION INTRODUCTION GPR Clutter Removal ANALYSIS
  • 29. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • FIR High Pass Filter
    Scenario C RAW DATA DATA AFTER SUBTRACTION INTRODUCTION GPR Clutter Removal ANALYSIS
  • 30. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • FIR High Pass Filter
    Scenario D RAW DATA DATA AFTER SUBTRACTION INTRODUCTION GPR Clutter Removal ANALYSIS
  • 31. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • Exponential Averaging
      • BG function of
        • Previous measurement
        • Previous BG calculation
      • A n-1 (t) , decays in the storage with an exponential
    Zetik, R., Crabbe, S., Krajnak, J., Peyerl, P., Sachs, J., Thoma, R., “Detection and localization of persons behind obstacles using M-sequence through-the-wall radar” INTRODUCTION GPR Clutter Removal ANALYSIS
  • 32. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • Exponential Averaging
      • Emphasizes recent events
      • Smoothes strong variations
      • Low memory and CPU required
      • Each estimated BG is stored
    Michael Bramberger, Roman Pflugfelder, Bernhard Rinner, Helmut Schwabach, Bernhard Strobl, “Intelligent traffic video sensor: architecture and applications” INTRODUCTION GPR Clutter Removal ANALYSIS
  • 33. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • Exponential Averaging
    α =0.3 Scenario A RAW DATA DATA AFTER SUBTRACTION INTRODUCTION GPR Clutter Removal ANALYSIS
  • 34. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • Linear Prediction
      • BG  Weighted linear function Previous traces
            • Future traces
      • Generalized Two-sided LP model
      • a p- and a p+  Linear prediction coefficients
    Jin-Jen Hsue and Andrew E. Yagle, “Similarities and differences between one-sided and two-sided linear prediction” INTRODUCTION GPR Clutter Removal ANALYSIS
  • 35.
    • Linear Prediction
      • Selection of p  Critical in performance
      • Estimation valid  A n-p (t)
      • or No target response
        • A n+p (t)
    LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES Thomas C. T. Chan, H. C. So, K. C. Ho, “Generalized two-sided linear prediction approach for land mine detection” A-scan under process A-scans involved in one background calculation INTRODUCTION GPR Clutter Removal ANALYSIS dx dy p p
  • 36. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • Linear Prediction
    p=8cm Scenario B RAW DATA DATA AFTER SUBTRACTION INTRODUCTION GPR Clutter Removal ANALYSIS
  • 37. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • Moving Average
      • Along-track sliding window N
      • A n (t) n=N
      • n=(N-1)/2
      • Window size related to length of hyperbolas
    F.P. Haeni, Marc L. Buursink, and John E. Costa, “Ground-penetrating radar methods used in surface-water discharge measurements” INTRODUCTION GPR Clutter Removal ANALYSIS dx dy Scan Direction A-scan under process A-scans involved in one averaging
  • 38. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • Moving Average
      • Non-changing part of signal considered as background
      • Based on two assumptions
        • Targets  Isolated scatterers
        • Constant roughness or smooth changes
    A. G. Yarovoy, P. van Genderen, and L. P. Ligthart, “Ultra-wideband ground penetrating impulse radar” INTRODUCTION GPR Clutter Removal ANALYSIS
  • 39. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • Moving Average
    N=17cm Scenario C RAW DATA DATA AFTER SUBTRACTION INTRODUCTION GPR Clutter Removal ANALYSIS
  • 40. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • Moving Median
      • Median replaces Mean
      • Median of a group of A-scans:
        • A a (tj)< A b (tj) <…, A c (tj), j=1,…,N T
        • Selection of central value
      • b n  Compilation of statistic medians for each time sample within the A-scans in window
      • Less sensitive to extreme changes than Moving Average
    Adel ElFouly, “Voids investigation at Gabbari Tombs, Alexandria, Egypt using ground penetrating radar technique” INTRODUCTION GPR Clutter Removal ANALYSIS
  • 41. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • Moving Median
    N=17cm Scenario C RAW DATA DATA AFTER SUBTRACTION INTRODUCTION GPR Clutter Removal ANALYSIS
  • 42. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • Weighted Moving Average
      • Enhances Standard Moving Average  Weights
      • Weights apply to each time sample
        • More weight to BG samples
        • Less weight to signal samples
      • Two averages are needed
    Ö. Yilmaz, Seismic Data Processing, Society of Exploration Geophysicists, Tulsa, 1987 INTRODUCTION GPR Clutter Removal ANALYSIS
  • 43. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • Weighted Moving Average
      • Processing Sequence
        • Preliminary Moving Average background subtraction
          • Small sliding window
        • Hilbert Transform
          • Envelope  Reflectivity strength
          • Instantaneous amplitudes   weighting coefficients
        • Moving Average using weights
          • Large sliding window
    Friedrich Roth, Convolutional Models for Landmine Identification with Ground Penetrating Radar INTRODUCTION GPR Clutter Removal ANALYSIS
  • 44. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • Weighted Moving Average
    N=13cm n=3cm Scenario B RAW DATA DATA AFTER SUBTRACTION INTRODUCTION GPR Clutter Removal ANALYSIS
  • 45. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • 7a) Shifted and Scaled Arbitrary Reference BG
      • Arbitrary b Ref (t) signal
      • Amplitude scale α
        • Max and Min b Ref (t) Max and Min A n (t)
      • Time shift t n,ref  Ground-air bounces overlap
    Friedrich Roth, Convolutional Models for Landmine Identification with Ground Penetrating Radar INTRODUCTION GPR Clutter Removal ANALYSIS
  • 46. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • 7a) Shifted and Scaled Arbitrary Reference BG
    Scenario A RAW DATA AFTER SUBTRACTION INTRODUCTION GPR Clutter Removal ANALYSIS
  • 47. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • 7b) Adaptive Shifted and Scaled BG in Freq. Domain
      • Original for Stepped Frequency Radar
      • Impulse Radar  Frequency domain FFT
      • Nonlinear minimization least squares criterion
    R. Wu, A. Clement, J. Li, E. G. Larsson, M. Bradley, J. Habersat, and G. Maksymonko, “Adaptive ground bounce removal” INTRODUCTION GPR Clutter Removal ANALYSIS
  • 48. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • 7b) Adaptive Shifted and Scaled BG in Freq. Domain
    Scenario D RAW DATA AFTER SUBTRACTION INTRODUCTION GPR Clutter Removal ANALYSIS
  • 49. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • 7c) Adaptive Shifted and Scaled BG in Time Domain
      • Time saving
        • Real signals
        • Single optimization for A-scan (instead of k)
      • Nonlinear minimization least squares criterion
    INTRODUCTION GPR Clutter Removal ANALYSIS
  • 50. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • 7c) Adaptive Shifted and Scaled BG in Time Domain
    Scenario B RAW DATA AFTER SUBTRACTION INTRODUCTION GPR Clutter Removal ANALYSIS
  • 51. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • Cylindrical Moving Average
      • 2D Moving Average
      • Circular averaging area N A-scans
        • Along-scan direction
        • Cross-scan direction
      • Spatial window  Cylinder (geometry of the problem)
    Jeroen Groenenboom, Alexander Yarovoy, “Data processing and imaging in GPR system dedicated for landmine detection” INTRODUCTION GPR Clutter Removal ANALYSIS
  • 52. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • Cylindrical Moving Average
    A-scan under process A-scans involved in one averaging Jeroen Groenenboom, Alexander Yarovoy, “Data processing and imaging in GPR system dedicated for landmine detection” INTRODUCTION GPR Clutter Removal ANALYSIS dx dy Scan Direction
  • 53. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • Cylindrical Moving Average
    Scenario A RAW DATA DATA AFTER SUBTRACTION INTRODUCTION GPR Clutter Removal ANALYSIS
  • 54. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • Principal Component Analysis
      • Any real matrix S  Subspaces orthonormal basis
      • U and V unitary matrices
      • σ 1 ,…,σ r ≥ 0 singular values of S (r=rank (S))
      • v i Vectors in V  Principal Components
      • Sliding window implementation
    Gilbert Strang, Linear Algebra and its Applications, Harcourt College Publishers, 3rd Edition, 1988 INTRODUCTION GPR Clutter Removal ANALYSIS
  • 55. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
    • Principal Component Analysis
    N=8.4cm λ =1 component Scenario C RAW DATA DATA AFTER SUBTRACTION INTRODUCTION GPR Clutter Removal ANALYSIS
  • 56. Background Removal in Array-Based UWB Radars for Landmine Detection
    • METHODS COMPARISON
    INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON
  • 57. METHODS COMPARISON
    • Numerical Criterion Applied
    S k, τ  target signal b k, τ  ground bounce INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON
  • 58. METHODS COMPARISON INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON
  • 59. METHODS COMPARISON INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON
  • 60. METHODS COMPARISON
    • FIR High Pass Filter
      • Study of performance straightforward  No parameters
      • SBR improvement larger in rough scenario
      • Time consumption very low
    • Exponential Averaging
      • Rough surface influence of weighting factor
      • Time consumption low
      • Storage previous background calculation
    • Linear Prediction
      • Large dependence on adjustable parameter p
      • When different target sizes  complicate detection
    INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON
  • 61. METHODS COMPARISON
    • Moving Average
      • Not able to remove reflections from rough surfaces
      • Influence of window is not critical in smooth scenarios
    • Moving Median
      • Generally improves SBR level of Moving Average for same window length
      • Large window size compared to hyperbola  degradation
    • Weighted Moving Average
      • Comparison with simple averaging  SBR
      • High SBR can be achieved  Accurate selection
      • Computational burden  Double averaging
    INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON
  • 62. METHODS COMPARISON
    • 7a) SaS Arbitrary Reference BG
      • Slowly changing surface  outperforms FIR, MAV and MM
      • Time consuming
    • 7b) Adaptive SaS BG in Freq.
      • Outstanding SBR values
      • Lower time consumption than cylindrical average or WMA
    • 7c) Adaptive SaS BG in Time
      • Improvement in SBR is high for a rough surface
      • High time of execution
    INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON
  • 63. METHODS COMPARISON
    • Cylindrical Moving Average
      • Remarkable results for a rough surface
      • Processing several array lines processing time
    • Principal Component Analysis
      • Complicated parametric study
      • Efficient implementation  time reduction
    INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON
  • 64. METHODS COMPARISON INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON Off line Sliding window n Sliding window m A k (t), k = 1 ,…, n A k (t), k = 1 ,…, m Moving Weighted On line/Off line Sliding window m A k (t), k = 1 ,…, m Moving Median On line/Off line Sliding window m A k (t), k =1,…, m Moving Average On line Prediction range p A n-p (t), A n+p (t) Two-Sided Linear Prediction On line Weighting factor α A n (t), b n-1 (t) Exponential Averaging On line None A n (t), A n-1 (t) FIR Filtering Recommended Application Algorithm Parameters A-scans involved in Background Model Algorithm features Algorithm/Technique
  • 65. METHODS COMPARISON INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON On line Sliding window m Number of components p A k (t), k <= p Principal Components Off line Averaging radius R A xy (t), x 2 + y 2 <= R 2 Cylindrical Moving Average Off line Time delay τ Amplitude scale α Sliding window m A Ref (t) Shifted and Scaled Time Domain On-line/Off-line Time delay τ Amplitude scale α Sliding window m A Ref (t) Shifted and Scaled Frequency Domain Off line Time delay τ Amplitude scale α A Ref (t) Shifted and Scaled Arbitrary Recommended Application Algorithm Parameters A-scans involved in Background Model Algorithm features Algorithm/Technique
  • 66. Background Removal in Array-Based UWB Radars for Landmine Detection INFLUENCE OF TECHNIQUES ON LANDMINE DETECTION INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE
  • 67. INFLUENCE OF TECHNIQUES ON LANDMINE DETECTION
    • SCENARIO AND DATA SET E
    INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE
  • 68. INFLUENCE OF TECHNIQUES ON LANDMINE DETECTION
    • SCENARIO AND DATA SET E
    INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE 5cm 0 2 NR22-AP semi 0 1.75 NR22-AP 5cm 10 1.5 NR22-AP 5cm -10 1.5 NR22-AP semi 10 1 NR22-AP semi -10 1 NR22-AP Depth Position Y Position X Target Location Object
  • 69. INFLUENCE OF TECHNIQUES ON LANDMINE DETECTION
    • FIR High Pass Filter
    INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE
  • 70. INFLUENCE OF TECHNIQUES ON LANDMINE DETECTION
    • Linear Prediction
    INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE
  • 71. INFLUENCE OF TECHNIQUES ON LANDMINE DETECTION
    • Moving Median
    INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE
  • 72. INFLUENCE OF TECHNIQUES ON LANDMINE DETECTION
    • Shifted and Scaled BG in Freq. Domain
    INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE
  • 73. INFLUENCE OF TECHNIQUES ON LANDMINE DETECTION
    • Principal Component Analysis
    INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE
  • 74. INFLUENCE OF TECHNIQUES ON LANDMINE DETECTION
    • EBR COMPARISON
    INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE 4.60 231.1741 1.0639E+3 Principal Components 4.23 827.2433 3.5014E+3 SaS Frequency Domain 9.15 211.9093 1.9409E+3 Median Filtering 9.26 49.0152 454.1735 FIR Filtering 12.48 448.1885 5.5976E+3 2-Sided LP EBR Background Energy Signal Energy Energy Feature Algorithm
  • 75. Background Removal in Array-Based UWB Radars for Landmine Detection CONCLUSIONS AND FUTURE WORK INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE CONCLUSIONS
  • 76. CONCLUSIONS AND FUTURE WORK
    • A number of algorithms developed for clutter removal in GPR
    • Difficulty to state quality objectively
      • Sort of terrain
      • Roughness
      • Material/size of targets
    • Performance Analysis after BG subtraction  SBR
    • Performance Analysis after migration  EBR
    • Computational Analysis  Off-line/On-line
    INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE CONCLUSIONS
  • 77. CONCLUSIONS AND FUTURE WORK
    • Best performance on smooth surface
      •  SaS in Frequency Domain
    • Best performance on rough surface
      • SaS in Time and Frequency Domain
      • Cylindrical Moving Average
    • Algorithms suggested for online processing
      • FIR filtering
      • Linear Prediction
      • Exponential Averaging
    • Less computationally expensive algorithm  FIR filter
    • Best performing algorithm after migration  L. Prediction
    INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE CONCLUSIONS
  • 78. CONCLUSIONS AND FUTURE WORK
    • Main results on this research:
      •  Optimal Background
    • Subtraction in GPR for Humanitarian Demining
    • European Radar Conference “EuRAD” (European Microwave week), October 2008
    INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE CONCLUSIONS
  • 79. CONCLUSIONS AND FUTURE WORK
    • Shifted and Scaled technique
      • Reference Background  New criteria
      • Time and Frequency Domain should equally perform
      • Accurate removal of antenna crosstalk
    • PCA showed reliability in other applications
      • More efficient implementation  online purposes
    • FIR filter
      • A larger number of coefficients may be included in filter implementation
      • Key issue  Coefficients selection
    INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE CONCLUSIONS
  • 80. CONCLUSIONS AND FUTURE WORK
    • 2-sided Linear Prediction
      • Tunable algorithm should be tested
      • Number of A-scans can be selected
    • Exponential Averaging should be analyzed after migration
      • Early tests revealed promising results
      • Alternative to Linear Prediction
      • Less dependency on parameters
      • Low overall energy after Focusing
      • High Energy-to-Background Ratio after Focusing
    INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE CONCLUSIONS
  • 81. Background Removal in Array-Based UWB Radars for Landmine Detection THANK YOU
  • 82. Background Removal in Array-Based UWB Radars for Landmine Detection
    • The IRCTR: An International Focus
  • 83. The IRCTR: An International Focus
    • IRCTR=Research center EEMCS of TUDelft
    • Main objective  Challenging scientific Telecom research Radar
    • Collaboration: Industries, scientific partners, Founding organizations
    • Research sectors  Program director
    • Emphasis on internationalization
    • Research cooperation with Europe, Asia and USA
  • 84. The IRCTR: An International Focus
    • Millimeter Wave Facilities
    • Support of Dutch Technology Foundation (STW)
    • Test and measurement facility for mm waves up to 110 GHz
    • Network vector analyzers
      • Agilent
      • ABmm
    • Anechoic chamber (DUCAT)
    Proof of Principle demonstrators at IRCTR
  • 85. The IRCTR: An International Focus
    • Wireless Communications
    • Real time OFDM code demonstrator
    • Transportable Radar for atmospheric remote sensing
    • FM-Continuous Wave (FMCW)
    • Crucial measurement facility
    • in CESAR
    Proof of Principle demonstrators at IRCTR
  • 86. The IRCTR: An International Focus
    • Detection of buried landmines
    • Since 1997  Dutch Ministry of Defense
    • Video impulse radar
    • Stepped frequency radar
    • Measurement and positioning
    • system
    Proof of Principle demonstrators at IRCTR
  • 87. The IRCTR: An International Focus
    • Program director: Alexander G. Yarovoy
    • Research areas
      • Properties of soils
      • Propagation and scattering of transmission fields
      • GPR Antennas
      • Radars
      • Target classification
      • UWB technology
      • Radar signal processing
    UWB Technology and Ground Penetrating Radar Group
  • 88. The IRCTR: An International Focus
    • Radiowave methods  Measurement of soil permittivity
    • Study of short-pulse scattering from dielectric targets and rough air-ground interface
    • UWB: bow-tie, spiral, TEM horns,
    • dielectric wedge antenna
    • UWB applications: Short range radar
          • UWB telecom
          • Near field sensors
    UWB Technology and Ground Penetrating Radar Group
  • 89. The IRCTR: An International Focus
    • Video Impulse Radars
    • Stepped Frequency Radars
    • Target classification
    UWB Technology and Ground Penetrating Radar Group