Humanitarian Demining with Ultra Wide Band Ground Penetrating Radar
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Transcript of Humanitarian Demining with Ultra Wide Band Ground Penetrating Radar
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Background Removal in Array-Based UWB Radars for Landmine
Detection
Delft University of Technology, The NetherlandsPublic University of Navarre, Spain
Álvaro Muñoz Mayordomo
Dr. Miguel Ángel Gómez LasoDr. Alexander G. Yarovoy
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CONTENTSI. INTRODUCTION: The Landmine Trouble Worldwide
II. GROUND PENETRATING RADAR IN HUMANITARIAN DEMINING
III. SCOPE OF THIS THESIS: Clutter Removal
IV. LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
V. METHODS COMPARISON
VI. INFLUENCE OF TECHNIQUES ON LANDMINE DETECTION
VII. CONCLUSIONS AND FUTURE WORK
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Background Removal in Array-Based UWB Radars for Landmine
Detection
INTRODUCTION: The Landmine Trouble Worldwide
INTRODUCTION
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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
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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
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INTRODUCTION: The Landmine Trouble Worldwide
Traditional Demining Techniques
• Prodders
• Metal Detectors
INTRODUCTION
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INTRODUCTION: The Landmine Trouble Worldwide
Traditional Demining Techniques
• Mine-Detection dogs
• Ground-engaging machines• Flails• Rollers• Millers and Tillers• Sifters• Dozers and graders
INTRODUCTION
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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
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Background Removal in Array-Based UWB Radars for Landmine
Detection
GPR IN HUMANITARIAN DEMINING
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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
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04/18/23 11INTRODUCTION GPR
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
n n nA t s t b t e
0 0.2 0.4 0.6 0.8 1
x 10-8
-1000
-500
0
500
1000
1500
Time [s]
Am
plitu
de [
mV
]
Antenna Crosstalk
Ground Bounce
Target Response
Antenna Crosstalk
n n nA t s t b t e
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04/18/23 12INTRODUCTION GPR
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
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GPR IN HUMANITARIAN DEMINING
Basic principles
B-Scan
Position [m]
Tim
e [s
]
0 0.1 0.2 0.3 0.4 0.5 0.6
0
1
2
3
4
5
6
7
8
9
x 10-9
-100
-50
0
50
100
B-Scan
Position [m]
Tim
e [
s]
0 0.1 0.2 0.3 0.4 0.5 0.6
0
1
2
3
4
5
6
7
8
9
10
x 10-9
-500
-400
-300
-200
-100
0
100
200
300
RAW DATA DATA AFTER SUBTRACTION
INTRODUCTION GPR
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GPR IN HUMANITARIAN DEMINING
Basic principles
B-Scan
Position [m]
Tim
e [s
]
0 0.1 0.2 0.3 0.4 0.5 0.6
0
1
2
3
4
5
6
7
8
9
x 10-9
-100
-50
0
50
100
DATA AFTER SUBTRACTION
DATA AFTER FOCUSING
INTRODUCTION GPR
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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
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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
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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
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Background Removal in Array-Based UWB Radars for Landmine
Detection
SCOPE OF THIS THESIS: Clutter Removal
INTRODUCTION GPR Clutter Removal
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SCOPE OF THIS THESIS : Clutter Removal
Ground Bounce and Antenna Effects Mitigation
0 0.2 0.4 0.6 0.8 1
x 10-8
-1000
-500
0
500
1000
1500
Time [s]
Am
plitu
de [
mV
]
0 0.2 0.4 0.6 0.8 1
x 10-8
-10
-5
0
5
10
15After Subtraction
Time [s]
Am
plitu
de [
mV
]
Antenna Crosstalk
Ground Bounce
Target Response
Ground Bounce
Target Response
Antenna Crosstalk
Antenna Crosstalk
INTRODUCTION GPR Clutter Removal
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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
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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
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SCOPE OF THIS THESIS : 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
INTRODUCTION GPR Clutter Removal
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Background Removal in Array-Based UWB Radars for Landmine
Detection
LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
INTRODUCTION GPR Clutter Removal ANALYSIS
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LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
Description of Test Scenarios
Data set
Scenario features
RoughnessNumber of
TargetsDepth Type of targets
A Flat 1 Surface Metal disk, 10cm
B Flat 7 Surface Metal/Plastic cylinders and pipe 5-10cm
C Quite flat 8 5cm Metal/Plastic/Cylinder, 10cm3 Plastic cylinders, 5.4cm
2 Plastic mines, 13cm
D Very rough 4 5cm Plastic mine 13cm; Plastic mine 8cm; one rock; one screw
E Rough with grass 6 Semi-buried and 5cm
Plastic mines, 12cm
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LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
1) High Pass Filter2) Exponential Averaging3) Linear Prediction4) Moving Average5) Moving Median6) Weighted Moving Average7) Cylindrical Moving Average8) Shifted and Scaled Background
1) Arbitrary Reference BG2) Frequency Domain3) Time Domain
9) Principal Component Analysis
INTRODUCTION GPR Clutter Removal ANALYSIS
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1) FIR High Pass Filter
• Two contiguous A-scans in background calculation
• Equally distributed weights
• High speed • Little memory usage
S. Nagwa, M. Bames, “A moving target detection filter for an ultra-wideband radar”
dx
dy
Scan Direction
LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
10.5n n n n ns t A t b t A t A t
0.5
An(t)
An-1(t)
bn(t)
INTRODUCTION GPR Clutter Removal ANALYSIS
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B-Scan
Position [m]
Tim
e [s
]
0 0.1 0.2 0.3 0.4 0.5 0.6
0
1
2
3
4
5
6
7
8
9
10
x 10-9
-15
-10
-5
0
5
10
15
LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
1) FIR High Pass Filter
10.5n n n n ns t A t b t A t A t
B-Scan
Position [m]
Tim
e [
s]
0 0.1 0.2 0.3 0.4 0.5 0.6
0
1
2
3
4
5
6
7
8
9
10
x 10-9
-500
-400
-300
-200
-100
0
100
200
300
Scenario A
RAW DATA DATA AFTER SUBTRACTION
INTRODUCTION GPR Clutter Removal ANALYSIS
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LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
1) FIR High Pass Filter
B-Scan
Position [m]
Tim
e [s
]
0 0.2 0.4 0.6 0.8 1 1.2 1.4
0
1
2
3
4
5
6
7
8
9
x 10-9
-4
-3
-2
-1
0
1
2
3
4
10.5n n n n ns t A t b t A t A t
B-Scan
Position [m]
Tim
e [s
]
0 0.2 0.4 0.6 0.8 1 1.2 1.4
0
1
2
3
4
5
6
7
8
9-200
-150
-100
-50
0
50
100
150
200
250
300
Scenario B
RAW DATA DATA AFTER SUBTRACTION
INTRODUCTION GPR Clutter Removal ANALYSIS
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LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
1) FIR High Pass Filter
B-Scan
Position [m]
Tim
e [s
]
0 0.5 1 1.5 2
0
1
2
3
4
5
6
7
8
9
10
x 10-9
-6
-4
-2
0
2
4
6
10.5n n n n ns t A t b t A t A t
Position [m]
Tim
e [s
]
B-Scan
0 0.5 1 1.5 2 2.5
0
1
2
3
4
5
6
7
8
9
10
x 10-9
-800
-600
-400
-200
0
200
400
600
800
1000
Scenario C
RAW DATA DATA AFTER SUBTRACTION
INTRODUCTION GPR Clutter Removal ANALYSIS
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LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
1) FIR High Pass Filter
B-Scan
Position [m]
Tim
e [s
]
0 0.2 0.4 0.6 0.8 1
0
1
2
3
4
5
6
7
8
x 10-9
-2
-1.5
-1
-0.5
0
0.5
1
1.5
10.5n n n n ns t A t b t A t A t
B-Scan
Position [m]
Tim
e [s
]
0 0.2 0.4 0.6 0.8 1
0
1
2
3
4
5
6
7
8
x 10-9
-8
-6
-4
-2
0
2
4
6
8
10
Scenario D
RAW DATA DATA AFTER SUBTRACTION
INTRODUCTION GPR Clutter Removal ANALYSIS
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LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
2) Exponential Averaging
• BG function of • Previous measurement• Previous BG calculation
• An-1(t), decays in the storage with an exponential
)()1()()( 11 tbtAtb nnn
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
2) Exponential Averaging
• Emphasizes recent events
• Smoothes strong variations
• Low memory and CPU required
• Each estimated BG is stored )()1()()( 11 tbtAtb nnn
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
2) Exponential Averaging
B-Scan
Position [m]
Tim
e [
s]
0 0.1 0.2 0.3 0.4 0.5 0.6
0
1
2
3
4
5
6
7
8
9
10
x 10-9
-500
-400
-300
-200
-100
0
100
200
300
B-Scan
Position [m]
Tim
e [s
]
0 0.1 0.2 0.3 0.4 0.5 0.6
0
1
2
3
4
5
6
7
8
9
10
x 10-9
-50
-40
-30
-20
-10
0
10
20
30
40
50
α=0.3Scenario A
)()1()()( 11 tbtAtb nnn RAW DATA DATA AFTER
SUBTRACTION
INTRODUCTION GPR Clutter Removal ANALYSIS
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LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
3) Linear Prediction
• BG Weighted linear function Previous traces
Future traces
• Generalized Two-sided LP model
• ap- and ap+ Linear prediction coefficients ( ) ( ) ( )n p n p p n pb t a A t a A t ;
Jin-Jen Hsue and Andrew E. Yagle, “Similarities and differences between one-sided and two-sided linear prediction”
INTRODUCTION GPR Clutter Removal ANALYSIS
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( ) ( ) ( )n p n p p n pb t a A t a A t ;
3) Linear Prediction
• Selection of p Critical in performance
• Estimation valid An-p(t) or No target
response An+p(t)
Thomas C. T. Chan, H. C. So, K. C. Ho, “Generalized two-sided linear prediction approach for land mine detection”
LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
A-scan under process A-scans involved in one background calculation
dx
dy
p
p
INTRODUCTION GPR Clutter Removal ANALYSIS
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LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
3) Linear Prediction ( ) ( ) ( )n p n p p n pb t a A t a A t ;
B-Scan
Position [m]
Tim
e [s
]
0 0.2 0.4 0.6 0.8 1 1.2 1.4
0
1
2
3
4
5
6
7
8
9-200
-150
-100
-50
0
50
100
150
200
250
300
p=8cm
B-Scan
Position [m]
Tim
e [s
]
0 0.2 0.4 0.6 0.8 1 1.2
0
1
2
3
4
5
6
7
8
9
x 10-9
-30
-20
-10
0
10
20
30
Scenario B
RAW DATA DATA AFTER SUBTRACTION
INTRODUCTION GPR Clutter Removal ANALYSIS
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LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
4) Moving Average
• Along-track sliding window N
• An(t) n=N
n=(N-1)/2
• Window size related to length of hyperbolas
1
2
1
2
Nk n
kN
k n
n
A t
b tN
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
4) Moving Average
• Non-changing part of signal considered as background
• Based on two assumptions• Targets Isolated scatterers • Constant roughness or
smooth changes
1
2
1
2
Nk n
kN
k n
n
A t
b tN
A. G. Yarovoy, P. van Genderen, and L. P. Ligthart, “Ultra-wideband ground penetrating impulse radar”
INTRODUCTION GPR Clutter Removal ANALYSIS
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LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
4) Moving Average
Position [m]
Tim
e [s
]
B-Scan
0 0.5 1 1.5 2 2.5
0
1
2
3
4
5
6
7
8
9
10
x 10-9
-800
-600
-400
-200
0
200
400
600
800
1000
B-Scan
Position [m]
Tim
e [s
]
0 0.5 1 1.5 2 2.5
0
1
2
3
4
5
6
7
8
9
10
x 10-9
-80
-60
-40
-20
0
20
40
60
80
N=17cm
n kb t mean A t k=1,..,N
Scenario C
RAW DATA DATA AFTER SUBTRACTION
INTRODUCTION GPR Clutter Removal ANALYSIS
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LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
5) Moving Median • Median replaces Mean• Median of a group of A-scans:
• Aa(tj)< Ab(tj) <…, Ac(tj), j=1,…,NT
• Selection of central value
• bn Compilation of statistic medians for each time sample within the A-scans in window
• Less sensitive to extreme changes than Moving Average
n kb t median A t
k=1,..,N
Adel ElFouly, “Voids investigation at Gabbari Tombs, Alexandria, Egypt using ground penetrating radar technique”
INTRODUCTION GPR Clutter Removal ANALYSIS
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04/18/23 41
LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
5) Moving Median k=1,..,N n kb t median A t
Position [m]
Tim
e [s
]
B-Scan
0 0.5 1 1.5 2 2.5
0
1
2
3
4
5
6
7
8
9
10
x 10-9
-800
-600
-400
-200
0
200
400
600
800
1000
B-Scan
Position [m]
Tim
e [s
]
0 0.5 1 1.5 2 2.5
0
1
2
3
4
5
6
7
8
9
10
x 10-9
-100
-80
-60
-40
-20
0
20
40
60
80
N=17cmScenario C
RAW DATA DATA AFTER SUBTRACTION
INTRODUCTION GPR Clutter Removal ANALYSIS
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LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
6) 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
1
1
n
i iin
ii
w xX
w
Ö. Yilmaz, Seismic Data Processing, Society of Exploration Geophysicists, Tulsa, 1987
INTRODUCTION GPR Clutter Removal ANALYSIS
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04/18/23 43
LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
6) Weighted Moving Average
Processing SequenceA. Preliminary Moving Average
background subtraction • Small sliding window
B. Hilbert Transform • Envelope Reflectivity
strength• Instantaneous amplitudes
weighting coefficients C. Moving Average using weights
• Large sliding window
1
1
n
i iin
ii
w xX
w
Friedrich Roth, Convolutional Models for Landmine Identification with Ground Penetrating Radar
INTRODUCTION GPR Clutter Removal ANALYSIS
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04/18/23 44
LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
6) Weighted Moving Average
B-Scan
Position [m]
Tim
e [s
]
0 0.2 0.4 0.6 0.8 1 1.2 1.4
0
1
2
3
4
5
6
7
8
9-200
-150
-100
-50
0
50
100
150
200
250
300
N=13cm n=3cm
B-Scan
Position [m]
Tim
e [s
]
0 0.2 0.4 0.6 0.8 1 1.2 1.4
0
1
2
3
4
5
6
7
8
9
10
x 10-9
-20
-15
-10
-5
0
5
10
15
20
25
1
1
n
i iin
ii
w xX
w
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 bRef(t) signal • Amplitude scale α
• Max and Min bRef(t) Max and Min An(t)
• Time shift tn,ref Ground-air bounces overlap , ,n n ref ref n refb t b t t
;
Friedrich Roth, Convolutional Models for Landmine Identification with Ground Penetrating Radar
INTRODUCTION GPR Clutter Removal ANALYSIS
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04/18/23 46
LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
7a) Shifted and Scaled Arbitrary Reference BG
B-Scan
Position [m]
Tim
e [
s]
0 0.1 0.2 0.3 0.4 0.5 0.6
0
1
2
3
4
5
6
7
8
9
10
x 10-9
-500
-400
-300
-200
-100
0
100
200
300
B-Scan
Position [m]
Tim
e [s
]
0 0.1 0.2 0.3 0.4 0.5 0.6
0
1
2
3
4
5
6
7
8
9
x 10-9
-100
-50
0
50
100
, ,n n ref ref n refb t b t t
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 ,
2
, , ,1
( , ) ( ) ( ) k n i
Kj
i n i n i n k n i n i kk
C x x e
@
,
,
*,
1
arg max ( ) ( ) k n i
n i
Kj
n i n i k n kk
x x e
:
,*
1,
2
1
( ) ( )
( )
n ik
Kj
n i k n kk
n i K
n i kk
x x e
x
:
:
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
B-Scan
Position [m]
Tim
e [s
]
0 0.2 0.4 0.6 0.8 1
0
1
2
3
4
5
6
7
8
x 10-9
-8
-6
-4
-2
0
2
4
6
8
10B-Scan
Position [m]
Tim
e [s
]
0 0.2 0.4 0.6 0.8 1
0
1
2
3
4
5
6
7
8
x 10-9
-3
-2
-1
0
1
2
3
4
,
2
, , ,1
( , ) ( ) ( ) k n i
Kj
i n i n i n k n i n i kk
C x x e
@
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
2
, , , ,
0
( , ) ( ) ( )T
i n i n i n n i n i n iC S t S t dt @
,
, ,
0
arg max ( ) ( )n i
T
n i n in i nS t S t dt
: ,
0,
2
0
( ) ( )
( )
T
n in i n
n i T
n i
S t S t dt
S t dt
:
:
INTRODUCTION GPR Clutter Removal ANALYSIS
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04/18/23 50
LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
7c) Adaptive Shifted and Scaled BG in Time Domain
B-Scan
Position [m]
Tim
e [s
]
0 0.2 0.4 0.6 0.8 1 1.2 1.4
0
1
2
3
4
5
6
7
8
9-200
-150
-100
-50
0
50
100
150
200
250
300B-Scan
Position [m]
Tim
e [s
]
0 0.2 0.4 0.6 0.8 1 1.2 1.4
0
1
2
3
4
5
6
7
8
9
x 10-9
-60
-50
-40
-30
-20
-10
0
10
20
30
40
2
, , , ,
0
( , ) ( ) ( )T
i n i n i n n i n i n iC S t S t dt @
Scenario B
RAW DATA AFTER SUBTRACTION
INTRODUCTION GPR Clutter Removal ANALYSIS
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04/18/23 51
LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
8) 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)
2 2 2
,
1,i j xy
x y R
b t A tN
Jeroen Groenenboom, Alexander Yarovoy, “Data processing and imaging in GPR system dedicated for landmine detection”
INTRODUCTION GPR Clutter Removal ANALYSIS
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04/18/23 52
LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
8) Cylindrical Moving Average
dx
dy
Scan Direction
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”
2 2
,1
1,i j xy
x y
b t A tN
INTRODUCTION GPR Clutter Removal ANALYSIS
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LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
8) Cylindrical Moving Average 2 2
,1
1,i j xy
x y
b t A tN
B-Scan
Position [m]
Tim
e [s
]
0 0.1 0.2 0.3 0.4 0.5 0.6
0
1
2
3
4
5
6
7
8
9
10
x 10-9
-40
-20
0
20
40
60B-Scan
Position [m]
Tim
e [
s]
0 0.1 0.2 0.3 0.4 0.5 0.6
0
1
2
3
4
5
6
7
8
9
10
x 10-9
-500
-400
-300
-200
-100
0
100
200
300
Scenario A
RAW DATA DATA AFTER SUBTRACTION
INTRODUCTION GPR Clutter Removal ANALYSIS
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LITERATURE OVERVIEW AND ANALYSIS OF TECHNIQUES
9) Principal Component Analysis • Any real matrix S Subspaces orthonormal
basis
• U and V unitary matrices • σ1,…,σr ≥ 0 singular values of S (r=rank (S))• vi Vectors in V Principal Components• Sliding window implementation
TS U V 1 rdiag ( , ... , )
1
( )n i ii
b t v
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
9) Principal Component Analysis
N=8.4cm λ=1 component
B-Scan
Position [m]
Tim
e [s
]
0 0.5 1 1.5 2
0
1
2
3
4
5
6
7
8
9
10
x 10-9
-100
-50
0
50
100
150
Position [m]
Tim
e [s
]
B-Scan
0 0.5 1 1.5 2 2.5
0
1
2
3
4
5
6
7
8
9
10
x 10-9
-800
-600
-400
-200
0
200
400
600
800
1000
1
( )n i ii
b t v
Scenario C
RAW DATA DATA AFTER SUBTRACTION
INTRODUCTION GPR Clutter Removal ANALYSIS
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04/18/23 56
Background Removal in Array-Based UWB Radars for Landmine
Detection
METHODS COMPARISON
INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON
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04/18/23 57
METHODS COMPARISON
Numerical Criterion Applied
2
,,
2
,,
max
max
S
B
kk L R
k Tk L T R
abs s t
SNBabs b t
0.6 0.8 1 1.2 1.4 1.6 1.8
0
2
4
6
8
10
x 10-9
REGION Rs
REGION Rb
LENGTH L
Sk,τ target signal
bk,τ ground bounce
INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON
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METHODS COMPARISON
-20
-15
-10
-5
0
dB
SBR for a smooth surface (C)
FIREXP. AVL. PRED.MOV. AVMOV-MEDW. MOV. AVSaS Arbit.SaS FREQ.SaS TIMECYLIND. MAVPCA
z
INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON
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METHODS COMPARISON
-12
-10
-8
-6
-4
-2
0
2
dB
SBR for a rough surface (D)
FIREXP. AVL. PRED.MOV. AVMOV-MEDW. MOV. AVSaS Arbit.SaS FREQ.SaS TIMECYLIND. MAVPCA
z
INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON
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METHODS COMPARISON
1) FIR High Pass Filter• Study of performance straightforward No parameters• SBR improvement larger in rough scenario• Time consumption very low
2) Exponential Averaging• Rough surface influence of weighting factor • Time consumption low • Storage previous background calculation
3) Linear Prediction• Large dependence on adjustable parameter p • When different target sizes complicate detection
10.5n n n n ns t A t b t A t A t
( ) ( ) ( )n p n p p n pb t a A t a A t ;
)()1()()( 11 tbtAtb nnn
INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON
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METHODS COMPARISON
4) Moving Average• Not able to remove reflections from rough surfaces• Influence of window is not critical in smooth scenarios
5) Moving Median• Generally improves SBR level of Moving Average for same
window length• Large window size compared to hyperbola degradation
6) Weighted Moving Average• Comparison with simple averaging SBR• High SBR can be achieved Accurate selection• Computational burden Double averaging
n kb t mean A t k=1,..,N
n kb t median A t k=1,..,N
1
1
n
i iin
ii
w xX
w
INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON
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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
, ,n n ref ref n refb t b t t
2
, , , ,
0
( , ) ( ) ( )T
i n i n i n n i n i n iC S t S t dt @
,
2
, , ,1
( , ) ( ) ( ) k n i
Kj
i n i n i n k n i n i kk
C x x e
@
INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON
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04/18/23 63
METHODS COMPARISON
8) Cylindrical Moving Average
• Remarkable results for a rough surface• Processing several array lines processing
time
9) Principal Component Analysis • Complicated parametric study• Efficient implementation time reduction
2 2
,1
1,i j xy
x y
b t A tN
1
( )n i ii
b t v
INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON
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04/18/23 64
METHODS COMPARISON
Algorithm/Technique
Algorithm features
A-scans involved inBackground Model
AlgorithmParameters
Recommended Application
FIR Filtering An(t), An-1(t) None On line
Exponential Averaging An(t), bn-1(t)Weighting factor
αOn line
Two-Sided Linear Prediction
An-p(t), An+p(t)Prediction range
pOn line
Moving Average Ak(t), k=1,…,m Sliding window m On line/Off line
Moving Median Ak(t), k=1,…,m Sliding window m On line/Off line
Moving WeightedAk(t), k=1,…,n
Ak(t), k=1,…,mSliding window nSliding window m
Off line
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04/18/23 65INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON
METHODS COMPARISON
Algorithm/Technique
Algorithm features
A-scans involved inBackground Model
AlgorithmParameters
Recommended Application
Shifted and Scaled Arbitrary
ARef(t) Time delay τAmplitude scale α
Off line
Shifted and Scaled Frequency Domain
ARef(t) Time delay τ
Amplitude scale αSliding window m
On-line/Off-line
Shifted and Scaled Time Domain
ARef(t) Time delay τ
Amplitude scale αSliding window m
Off line
Cylindrical Moving Average
Axy(t), x2+y2<=R2 Averaging radius
R Off line
Principal Components Ak(t), k<=p Sliding window m
Number of components p
On line
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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
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INFLUENCE OF TECHNIQUES ON LANDMINE DETECTION
• SCENARIO AND DATA SET E
Position [m]
Tim
e [
s]
B-Scan
0 5 10 15 20 25
0
2
4
6
8
x 10-9
-200
0
200
INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE
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INFLUENCE OF TECHNIQUES ON LANDMINE DETECTION
• SCENARIO AND DATA SET E
Object Target Location
Position X Position Y Depth
NR22-AP 1 -10 semi
NR22-AP 1 10 semi
NR22-AP 1.5 -10 5cm
NR22-AP 1.5 10 5cm
NR22-AP 1.75 0 semi
NR22-AP 2 0 5cm
Scan line [m]
Arr
ay lin
e [
m]
Moving Median Filter
0.9 1 1.1
-0.2
-0.1
0
0.1
0.2
-10
-5
0
INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE
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INFLUENCE OF TECHNIQUES ON LANDMINE DETECTION
1) FIR High Pass Filter
INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE
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INFLUENCE OF TECHNIQUES ON LANDMINE DETECTION
2) Linear Prediction
INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE
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INFLUENCE OF TECHNIQUES ON LANDMINE DETECTION
3) Moving Median
INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE
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INFLUENCE OF TECHNIQUES ON LANDMINE DETECTION
4) Shifted and Scaled BG in Freq. Domain
INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE
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INFLUENCE OF TECHNIQUES ON LANDMINE DETECTION
5) Principal Component Analysis
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INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE
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INFLUENCE OF TECHNIQUES ON LANDMINE DETECTION
EBR COMPARISON
Algorithm Energy Feature
Signal Energy
Background Energy
EBR
2-Sided LP 5.5976E+3 448.1885 12.48
FIR Filtering 454.1735 49.0152 9.26
Median Filtering 1.9409E+3 211.9093 9.15
SaS Frequency Domain 3.5014E+3 827.2433 4.23
Principal Components 1.0639E+3 231.1741 4.60
INTRODUCTION GPR Clutter Removal ANALYSIS COMPARISON INFLUENCE
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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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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
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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
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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
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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
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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
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Background Removal in Array-Based UWB Radars for Landmine
Detection
THANK YOU
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Background Removal in Array-Based UWB Radars for Landmine
Detection
The IRCTR: An International Focus
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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
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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
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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
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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
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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
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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
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The IRCTR: An International Focus
• Video Impulse Radars• Stepped Frequency Radars• Target classification
UWB Technology and Ground Penetrating Radar Group