This document discusses analysis of ground-penetrating radar (GPR) data from single-channel and multi-channel surveys. It finds that channel 4 of the multi-channel GPR system produces low amplitudes, making air-wave picking imprecise. Placement of antenna cables on the center vs. side of the sled also affects air-wave arrival times. Semblance analysis, used to pick ground waves, breaks down under non-linear waves, use of selected traces only, and gained data. The source of uncertainty in GPR data includes skipped traces and temporal drift of time-zero corrections between measurements.

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GPR MC/WARR Calibration:
t0-Correction Analysis of Single-channel
vs. Multi-channel Surveys
(Final Update)
Tuesday, August 16th, 2016 | Kevin Fan

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-Ground Wave is identified** in WARR trace, then cross-
correlated with the corresponding MC trace; the
“MC/WARR time-shift“ is then the time corresponding
to the maximum cross-correlation value 2
Context
-Previous Work:
a) Cross-Correlation Analysis of Baxter‘s July 2015 Selhausen MC/WARR Data*
(“t0-correction Update Pres” in FZJ-GPR)
-Overall Objective: To determine whether 500MHz multichannel GPR data can be calibrated
with CMP data acquired at corresponding locations, via modification of the t0-correction
-Based upon intuitive hypothesis that traces of the 2 surveys, at the same locations, are
similar but just time-shifted version of one another

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Context
 Results:
-Same procedure is iterated over all other channels at the specific location, then
all channels at each and every other location
-A general, channel-specific t0-correction could not be established, due to evident
heterogeneity in the time-shift at different CMP locations along the 120m line
-Mix of time shifts both positive and negative; whereas a systematic shift
between MC/CMP data should be only one or the other?
-Necessitates focus upon only a few locations for subsequent measurements…

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b) Analysis of July 2016 Selhausen MC/WARR Data, including new MC-calibration
Measurements (Location=5m)
(“MC-Calibration Update” in FZJ-GPR)
-Channel 4 produces very low amplitudes, as well as energies (sum of squared amplitudes)
relative to other channels
-Script MC_calib_processing produces amplitude/energy plots, plots temporal cross-correlation
between measurements taken at different times, and wiggle (as opposed to colour traces)
-Can choose to exclude any combination of undesirable channels/positions from analysis
Context
Apply Channel-specific t0-correction

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*As determined by manual picking of 1st air-wave arrivals
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ContextResults:
-Calculated expected air-wave arrival times for every channel/location, based on
theoretical air wave velocity (0.2997m/ns)
-For any particular location on the MC-sled:
t0-Correction = Measured arrival time* - Theoretical arrival time
-Typically, channels 1/2/3/6 have similar t0-correction values, while channels 4/5/7
are also similar, albeit delayed relative to channels 1/2/3/6
-Chose to exclude Location 1 (at 23cm on MC-sled) for all channels, due to difficulties
in manual air-wave picking arising from near-field effects (see next slide)

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Rationale for Dumping Position 1 (of all channels)
-Too early: t0-
correction too
small relative to
other positions
-Too late: t0-
correction too
large relative to
other positions

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Calculation of Cross-Correlation
Coefficient for Quantitative Measure
of Deviation in Traces over Time-
Spans of a few seconds
(at 5m vs. 110m along profile)
-Position 1 removed from analysis
-Generally (except for Channel 4), value is >0.97,
indicating high degree of temporal self-similarity
(over scales of several seconds)

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Current Work: Data Comparison of
July 2016 Selhausen Measurements
Definitions
-Full WARR: Data that, aside from skipped traces, encompasses a continuous
range of offsets
-7 traces WARR (3 forms):
a) MC-sled I: Measurements taken with the MC-sled (termed “MC
-calibration measurements), during which a single-channel WARR is
performed for each and every channel (by varying the Rx-position
over all positions in the MC-sled, for each channel)
b) MC-sled II: Full WARR in MC-sled, that has later (via processing)
been reduced to the subset of 7 traces corresponding to MC positions
c) PE-sled: Same as (b), but with PE-sled
-PE-sled: Measurements taken with the Pulse Ekko single-channel sled
-MC-sled: Measurements taken with the custom multichannel sled
-Channel: A particular transmitter/receiver combination (eg. Tx/Rx4)
-Position/Location: The specific section into which Rx is placed

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Current Work: Data Comparison of
July 2016 Selhausen Measurements
Field Conditions/Measurements
-See spreadsheet Selhausen-04-07-MC in FZJ-GPR for detailed information regarding data files
-Field Measurements taken on 04/07/2016 with Manuela, Anja, Jan; survey design by Manuela
-Weather: Hot, sunny day with no rain
-DVL battery was running low for later measurements (ie. during CMP’s, 110m MC-calibration)
Data Processing Considerations
-Location of Interest: 5m along 120m profile (where 0m is the side closest to the street)
-Only performed all survey methods with Channel 1; Channels 2-6 were only used for MC-
calibration measurements at 5m and 110m, as well as for MOG of the entire 120m profile
-All traces dewowed (calls script dewow_anja_eso.m), ungained, and normalized to
max(abs(‘trace’))=1, to allow for comparison between MC/WARR data
-RPE_Evan.m indicates no skipped traces for MC-calibration data
-Output/Plots generated by script MC_calib_processing.m in main folder
-Semblance Analysis Parameter Space:
a) Ground Wave
- t0 ∈ (0,5) ns
- v ∈ (0.05,0.15*) m/ns
b) Air Wave (newly implemented)
- t0 ∈ (1.5,5.0) ns
- v ∈ (0.25,0.30) m/ns
a)/b) Parameters for both Air/Ground Waves
*Time width = 24ns (arbitrary..?)

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Script Documentation
GPR_Summer_2015_MC - Main script for MOG MC data along profile; must specify data
folder + line (only 1 permitted)
-Accounts for skipped traces by removing them, then compressing the data-set
-Only need to do air-wave picks once; upon completion, will save and use picks
in future
To redo picks, delete t0AirOffsets.mat
Velocity_Analysis_MC_Automated- Called by above - main script for automated ground-
wave picking from MC-data (semblance takes in as input each ‘7-trace WARR’ taken by
the MC system); includes t0-correction and no smoothing
MC_calib_processing – Script to process 7-trace WARR (MC-sled I) data
-Can choose whether to do manual air-wave picks or automated ones (ie. air-
wave semblance); ground-wave picking automated via semblance
-Can exclude any combination of channels/positions from analysis in section
‘Data Parameters’, sub-section ‘MC-calibration Parameters’
Velocity_Analysis_MC_Automated_calib – Similar to Velocity_Analysis_MC_Automated,
but for 7-trace WARR (MC-sled I) data
Velocity_Analysis_MC_Automated_calib_wiggle – Same as above, visualized as
wiggle-traces rather than colour plots
Velocity_Analysis_MC_Automated_calib_wiggle_airground – Same as above, with
automatic air-wave semblance picking instead of manual air-wave picking

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Script Documentation
GPR_Summer_2015_WARR – Main script for WARR data (of form MC_sled II or PE_sled)
-Smooths data (5-point moving average)
Saves air-wave picks; to redo, delete xairpicks or tairpicks (deleting either one
will re-write both)
vel_ana_TE_CO_CMP_Multi_Automated – Called by above; automatic pick of maximum
semblance to determine ground wave
vel_ana_TE_CO_CMP_Multi_Comp – Similar to above, but with manual pick of maximum
semblance (Igor has incorporated into his scripts)
CMPandMC_correlation – Main script used previously for cross-correlation analysis of
Baxter’s July 2015 Selhausen data
PlotAllSelectTraces – Plots the 3 types of 7-trace WARR surveys (see (a)/(b)/(c) in
‘Definitions’) at all offsets

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PE-sled
(Source Data:
Folder 19,
LINE00.DT1)
MC-sled
(Source Data:
Folder 19,
LINE55.DT1)
Full WARR, pre-t0-correction, gained: PE vs. MC Sleds
 Which to pick as Air-wave Arrival: High-frequency or low-frequency content?

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-t0-correction now
applied, based on
direct air-wave pick
(value displayed at
bottom of plots)
-Semblance analysis
used to (attempt to)
identify ground wave
(bolded line on plots)
T0-correction +
Corresponding
Semblance
(High-freq.
air picks)
PE-sled
MC-sled

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Analogous
plots for Low-
Freq. air picks
PE-sled
MC-sled
-Difference in t0-
correction when choosing
high vs. Low-freq. Air
wave is ~6ns for both
PE/MC-sleds
-PE-sled pick appears
~correct (characterizing
the ground wave
minimum)
-MC-sled pick in-correct;
ostensibly requires
inclusion of negative
intercept-time in
semblance parameter
space?

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11:05
15
Full WARR PE-sled, at Different Time, t0-corrected/gained
11:09 12:56
-Compare whether picking high vs. low frequency air-wave has effect upon
temporal variation of t0 (over the course of the day)
High-frequency Picks

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11:05
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Full WARR PE-sled, at Different Time, t0-corrected/gained
11:09 12:56
-t0 values larger for low-frequency picks
Low-frequency Picks

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-For low-frequency picks, max
semblance (and associated
values of t0/v) are far more
consistent, than amongst high-
frequency picks
 Implies that minimization of
temporal variability requires
picking of low-frequency air-
waves, even if earlier high-
frequency content is present
Corresponding
Semblance Plots
High-frequency
picks
Low-frequency
picks
11:05
11:05
11:09
11:09 12:56
12:56

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-t0-correction now relies upon (newly implemented) air-wave
semblance, replacing manual picking
General Proviso: Automatic air-wave picking requires fine-
tuning of parameter space!
-Chosen intercept time from air-wave semblance typically
too small (ie. Needs to be later to accurately plick 1st-
break)
-Optimal parameter space here is:
v ∈ (0.25* , 0.30) m/ns
t ∈ (0.18 , 5) ns
-No set of parameters tested thus far has resulted in 100%
accurate picking: typically there is a pattern in which though
most channels are fine, a few channels will have their automatic
pick being too early, for all locations at such channels (for
instance, the plots on Slide 20)
7-trace WARR (MC-sled): Gained vs. Ungained

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Gained
Air Wave,
Traces
Gained
Ground Wav
Traces
Air Wave
Semblance
(of gained data)
Ground Wave
Semblance
(of gained data)

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Ungained
Ground Wave
Traces
Ungained
Air Wave
Traces
Ground Wave
Semblance
(of ungained data)
Air Wave
Semblance
(of ungained data)

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-Gaining of 7-trace WARR (MC-sled) data results in ambiguous
semblance plot (very high-values across parameter space, no
clear maximum), while ungained data contains several peaks
Observations

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Plotted in ‘PlotAllSelectTraces.m’ 22
Qualitative Comparison of
Different GPR Survey Methods

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Effect of Running the Cables over the
Centre vs. Side of the MC-sled (gained,
normalized, non-t0 corrected)
Centre Side

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Observations
-Effect of cable position appears significant, and may
affect accuracy of both air and ground wave picks
though it appears to influence the presence of early
-Channel 1: Plots for both positions identical upon
visual inspection
-Channels 2-6: 1st-break air wave arrival appears to be
delayed when cables on side, relative to those for the
cables on centre
-Can further investigate with cross-correlation, see if
cable position has influence on semblance results,
etc..
 Require a ‘cable-holder’ that will allow for centre
position to be employed?

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Discussion: Sources of Uncertainty
a) Skipped Traces: Typically a few skips per CMP – if too many skips, can distort
linearity of air/ground wave, and therefore distort the t0 obtained from semblance
-Current method used in Ekko2Dread2_Update_test removes skipped
traces, then collapses data to remove the holes
-Offset information in header files has been corrected, to account for
skipped traces
-However, the data is not located in the correct position (offset), due to
collapsing approach
-Proposed Solution: Rather than collapsing data, fill in holes via
interpolation (eg. spline)
-See “On Recovering Missing Ground Penetrating Radar Traces by
Statistical Interpolation Methods” (Safont et. al. 2014) for inspiration?
b) Temporal Variation of t0 even for the same Survey Type*: Across multiple
measurements over the same day of the same thing (Full WARR at 5m in PE-
sled), is variable (see next slide)
-Possibilities: Instrumental temporal drift, use of high-frequency air
waves during manual picking
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Conclusions
Analysis of Channels in the Multichannel GPR System
-Channel 4 is faulty (very low amplitude/energy), rendering air-wave picking
(and consequently t0-correction) highly imprecise
-Channels 5/7 have sufficient energy, but on average have larger t0-values
than channels 1/2/3/6
-The channel-specific t0-correction may be dependent upon the specific
subsurface conditions at the location (eg. high-conductivity), as implied by the
fact that the 110m calibration measurements showed that even for different
positions of the same channel, t0 was variable; while calibration at 5m
produced much more consistent results
-Attempted CMP measurements with the Multiplexer failed
-Placement of the MC antenna cables on the middle vs. side of the sled
appears to have a significant effect for Channels 2-6, with the side positioning
resulting in a delayed air-wave 1st-break

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Conclusions
Semblance Analysis
-Semblance analysis breaks down (manifested by non-unique maxima,
non-physically reasonable parameters chosen,etc.) under circumstances
such as:
-Wave non-linearity (whether due to skips or otherwise)
-Use of only selected traces (eg. In MC)
-Gaining of data (for 7-trace WARR with the MC-sled)
-Generally, the Semblance Parameter space must be tested for each
data-set
-It is not always clear that 5ns is optimal as the maximum possible
intercept-time for 500MHz data; as max semblance values sometimes
occur at the edge of the parameter space
-Time-width (current default value of 24ns seems arbitrary)
Temporal Variation
-Temporal variation in data on the scale of several seconds is minimal,
as indicated by cross-correlation calculations; regarding diruanl
variations, the t0-correction value is also consistent, but only provided
that the low-frequency air-wave arrivals are chosen

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1. Apply the Channel-1 t0-calibration results to other channels; repeat
semblance, see if results are consistent across channels
2. Apply channel-specific t0-corrections (calculated from
MC_calib_processing.m) to the 120m profile MOG data, then see if
ground-wave semblance values become comparable with WARR data
taken at same positions
3. Perform 7-trace WARR (MC-sled) measurements at locations with a
range of conductivities, so as to better characterize the degree to which
the consistency of the channel-specific t0-correction is affected by
specific subsurface conditions at each location
Future Directions

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4. Implement potential Semblance Solutions, such as:
-Application of Hilbert Transform to 7-trace WARR (PE-sled)
may be an avenue for improvement of semblance and reduction of non-
uniqueness of maxima
-Investigation of the influence of Time-width (‘window’) on max
semblance picks
-Include negative time values in semblance parameter space?
5. Investigate proper treatment of skipped traces, via interpolation
6. Use filtering to improve air-wave picking, such as band-pass, to
remove high-frequency content sometimes seen, as well as low-
frequency waves that occur before the air wave
7. Construct/Upgrade MC-sled such that all antenna cables may be run
through the centre of the sled
Future Directions