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.
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
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
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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
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LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
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)
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LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
FIR High Pass Filter
Scenario A RAW DATA DATA AFTER SUBTRACTION INTRODUCTION GPR Clutter Removal ANALYSIS
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LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
FIR High Pass Filter
Scenario B RAW DATA DATA AFTER SUBTRACTION INTRODUCTION GPR Clutter Removal ANALYSIS
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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
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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
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LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
Exponential Averaging
α =0.3 Scenario A RAW DATA DATA AFTER SUBTRACTION INTRODUCTION GPR Clutter Removal ANALYSIS
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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
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
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LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
Linear Prediction
p=8cm Scenario B RAW DATA DATA AFTER SUBTRACTION INTRODUCTION GPR Clutter Removal ANALYSIS
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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
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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
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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
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LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
Friedrich Roth, Convolutional Models for Landmine Identification with Ground Penetrating Radar INTRODUCTION GPR Clutter Removal ANALYSIS
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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
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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
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LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
7a) Shifted and Scaled Arbitrary Reference BG
Scenario A RAW DATA AFTER SUBTRACTION INTRODUCTION GPR Clutter Removal ANALYSIS
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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
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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
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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
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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
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LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
Cylindrical Moving Average
Scenario A RAW DATA DATA AFTER SUBTRACTION INTRODUCTION GPR Clutter Removal ANALYSIS
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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
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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
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Background Removal in Array-Based UWB Radars for Landmine Detection
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
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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
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Background Removal in Array-Based UWB Radars for Landmine Detection INFLUENCE OF TECHNIQUES ON LANDMINE DETECTION INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE
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
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Background Removal in Array-Based UWB Radars for Landmine Detection CONCLUSIONS AND FUTURE WORK INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE CONCLUSIONS
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