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The Effects of Reflector Geometry on Radar Data Acquisition
International Symposium on Radioglaciology 9/09/2013
Nicholas Holschuh, Sridhar Anandakrishnan, Knut Christianson
Intr
oduct
ion
Sta
ckin
gR
efr
act
ion
Objectives of RESC
oncl
usi
on
sR
. Pa
ttern
Historic Objectives
•Determine the depth to (and geometry of) the basal reflector
•Describe the internal structure of the ice sheets using the internal reflecting horizons (IRHs)
Modern Objectives
•Use return powers from basal reflectors to determine dielectric properties of the ice-bed interface
•Analyze the spectral quality of reflectors to uniquely identify layers through space
Intr
oduct
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Sta
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efr
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MotivationC
oncl
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sR
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Intr
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MotivationC
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The brightest reflectors are sometimes traceable through the lossy region …but at other times, are completely lost in the noise…
Intr
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MotivationC
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sR
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What is the source of the data loss?
- Affects deeper reflectors more than shallow ones- Appears to be related to reflector slope- More prevalent in the High Frequency Airborne Data
Intr
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MotivationC
oncl
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Intr
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Sta
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MotivationC
oncl
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sR
. Pa
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Intr
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Sta
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MotivationC
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Intr
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Assumptions - Specularity
Concl
usi
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sR
. Pa
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Internal Reflectors: Specular(Obey the Law of
Reflection)
Basal Reflectors: Diffuse
Reflection Coefficient
Reflection Coefficient +
Angular Distribution
Refr
act
ion
Sta
ckin
gIn
troduct
ion
Beam FocusingC
oncl
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on
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. Pa
ttern
Ground Survey
Airborne Survey
n = 1 + 0.851ρ
Refr
act
ion
Sta
ckin
gIn
troduct
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Beam FocusingC
oncl
usi
on
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. Pa
ttern
Ground Survey Airborne Survey
Refraction Limits:
Ground Survey – 49ºAirborne Survey – 34º
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efr
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StackingIn
troduct
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ttern
Sta
ckin
g
Com
ponent
Tra
ces
Sup
eri
mpose d
C
om
ponents
Sta
cked T
race
(N
orm
aliz
ed)
Ideal S
tack
(Norm
aliz
ed)
Concl
usi
on
sR
efr
act
ion
StackingIn
troduct
ion
R. Pa
ttern
Sta
ckin
g
Com
ponent
Tra
ces
Sup
eri
mpose d
C
om
ponents
Sta
cked T
race
(N
orm
aliz
ed)
Ideal S
tack
(Norm
aliz
ed)
Stacking Controls
1) Radar Frequency2) Reflector Dip3) Stacking Distance
Concl
usi
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Stacking – 1m Posting Interval
Intr
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R. Pa
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Sta
ckin
g
Concl
usi
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sR
efr
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Stacking – 1m Posting Interval
Intr
oduct
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R. Pa
ttern
Sta
ckin
g 0.863
Concl
usi
on
sR
efr
act
ion
Stacking – 10m Posting Interval
Intr
oduct
ion
R. Pa
ttern
Sta
ckin
g 0.018
Concl
usi
on
sR
efr
act
ion
Stacking – 10m Posting Interval
Intr
oduct
ion
R. Pa
ttern
Sta
ckin
g 0.202
Concl
usi
on
sR
efr
act
ion
Stacking – 20m Posting Interval
Intr
oduct
ion
R. Pa
ttern
Sta
ckin
g 0.009
Concl
usi
on
sR
efr
act
ion
Stacking – 10m Posting Interval
Intr
oduct
ion
R. Pa
ttern
Sta
ckin
g
0.00090.00210.01790.01950.04681
0.00260.02240.02950.03020.08211
0.01180.02520.03020.04790.09851
0.02250.04050.07090.09850.20271
0.94620.96190.97680.98910.9971
Concl
usi
on
sR
efr
act
ion
Stacking Amplitude LossIn
troduct
ion
R. Pa
ttern
Sta
ckin
g
Sta
ckin
gR
efr
act
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Radiation PatternIn
troduct
ion
Concl
usi
on
sR
. Pa
ttern
Describes the angular distribution of the gain for a given radar antenna (Typically optimized for Nadir)
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ckin
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Radiation PatternIn
troduct
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Concl
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Caveats - SpecularityIn
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Concl
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Offsets 0 – 1400m (100m)
Transmitter
Receiver
Sta
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ConclusionsIn
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ttern
Concl
usi
ons
Areas of intense deformation (and therefore glaciological interest) are prone to internal data loss
Amplitude loss due to reflector geometry should be corrected for if dipping beds are used in amplitude analysis.
Loss is ultimately a function of radar design and data collection methods. Choosing appropriate radars (frequency), platform, and stacking
distances can minimize data loss.
Nicholas Holschuh – [email protected]
Advisors: Sridhar Anandakrishnan
Richard Alley
Collaborator: Knut Christianson
Questions?
This material is based upon work supported by the National Science Foundation Graduate
Research Fellowship Program under Grant No. DGE1255832.
We would like to acknowledge the use of data products from CReSIS generated with support from NSF grant ANT-0424589 and NASA grant NNX10AT68G.
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