phd final slides
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Ph.D. thesis presentation by Andrea Barucci Advancements on interferometric radar: studies and applicationsTRANSCRIPT
Advancements on interferometric radar: studies and applications
Coordinatore: Prof. Carlo Atzeni
Tutor: Prof. Massimiliano Pieraccini
Candidato: Andrea Barucci
CorsodiDottorato
in IngegneriadeiSistemiElettronici
XXIII ciclo
Introduction
Applicationofadvancedmonitoringtechniquesto the monitoring and
characterizationofquarriesfor the profit optimization and for the
safety and environmentalprotectionof the quarrymining
CWSF Ground BasedSynthetic Aperture Interferometric radar
CentralFrequency 16.75 GHz
Banwidth 400 MHz
Tx Power 26 dBm EIRP
SAR scan length 2 m
SAR acquisition time 4 min (minimum)
Power consumption < 40 W
Radar installation
Powersupply system
Wide angle SAR
Start 16 feb 2009
End 25 mar 2009
Days of measurement 39
N. Radar acquisitions about 600 (1 every 2 hours)
Measurementcampaign
RCS SAR image
Range
resolution
0.5 m
Cross
range
resolution
5mrad
Interferograms in scarp area
(m) (m) (m)
(m)(m)(m)
(m)
(m)
(m)
(m)
(m)
(m)
Eachinterferogramrelatesto a timelapseoftwohours
Interferometricanalysisin the wallarea
1. PSsselection
DispersionIndex
2.
Atmosphericmeanphasescreen
removal3. Calculationofdisplacements
About 50.000 PSsselected in
all the area
Interferometricanalysis in the wallarea
cum
ula
ted
dis
pla
cem
ent
Timeperiod: 23 days
Selectionof 50 pixels in the wall
Interferometricanalysis in the wallarea
cum
ula
ted
dis
pla
cem
ent
Timeperiod: 3days
Selectionof 50 pixels in the wall
Validationof the methodby a corner reflector
Distance: 800 m
Actual
(mm)
Measured
(mm)
Error
(mm)
2.0 2.05 0.05
1.0 0.89 0.11
0.5 0.53 0.03
Interferometric DEM of the quarry
Radar
Laser
Conclusions• A ground based Synthetic Aperture Interferometer was
successfully tested for the first time in a quarry.
• The system showed an accuracy of few tenths of a millimeterin displacement’s measurement, over a long period and at800 meters of distance.
• In short term measurements a simulation showed anaccuracy in measurement of displacements of the order of atenth of a millimeter.
• DEM reconstruction showed some limitations especially inhigh slopes.
S. T. Bramwell, P. C.W. Holdsworth, and J.-F. Pinton,
Universality of rare fluctuations in turbulence and critical
phenomena, Nature 396, 1998
Physical Review Letters [2000, 2005, 2008]
• Long term atmospheric artifacts on GB-SAR are known
• Radar signal propagation through tropospheric turbulence is a new
research topic
Data
Analysis
Classic:Fluctuations of signal
as a function of
turbulence
Modern:Correlated systems,
Gumbel statistics
Experiment
Universal fluctuations in tropospheric radar measurements
Introduction
Firenzuola scenario
Scenario and raw-data
CR distance
Ultrasonic Anemometer / Weather sensor
Radar sampling freq Range Resolution
Observational time
65 m 4/1Hz About 50 Hz 1 m 6 h
Detrending – High-pass filter
• Turbulent phenomena occur
at the micro scale,
corresponding to distances
shorter than 1 km, which are
the usual working distances for
a GB-SAR.
• We use a moving average to
remove the fluctuations on
temporal scales greater than 30
minutes
Time series data analysis
We use overlapping
temporal windows, with
length of about 30
minutes:
- About 10^5 points ->
rare fluctuations & good
statistics
- Constant Reynolds
number
Turbulent Kinetic
Energy (TKE) is a
measure of the
turbulence
Wind fluctuations dependency
R = 0.98 R = 0.89
Radar signal statistics & Correlated Systems
Correlated
Systems
Turbulence
Ising& 2D XY
Forest fires,
etc.
River water
level
Radar signal through a
turbulent atmosphere
Global quantity
Generalized
Gumbel PDF
Radar Data
statistics?
Generalized Gumbel
• Generalized Gumbel describes the fluctuations in Correlated Systems, its
shape depends on a real parameter a
• As a varies, the shape of the distribution varies from a completely
asymmetric, negatively skewed, distribution to a symmetric one quite similar
to a Gaussian function
• The parameter a has been proposed to be inversely related to the correlation
length of the system
Data distribution
• Fit of the data with the GG(a)
• Amplitude statistic appears to fit with the GG
• Phase statistic doesn’t show the same behaviour
• The radar data distributions calculated over the analysis windows show different means and standard deviations new method from Nature
Amplitude
Phase
• a is determined by the turbulence strength
• In hard windy conditions, a is nearly equal to pi/2 which is the value
for which GGa is approximately the Bramwell-Holdsworth-Pinton
distribution observed in turbulence and critical systems
Andrea Barucci
Conclusions
• The radar signal statistic:
– It is influenced by the turbulence
– It is a global quantity able to measure the “correlation of the
atmosphere” at the micro-scale
• We confirm the adequacy of the Gumbel statistic to describe
highly correlated complex systems
• SAR images - turbulence: work in progress• Paper published by Europhysics Letters: A. Barucci, G. Macaluso, D. Mecatti, L. Noferini, D. Fanelli, A.
Facchini, M. Materassi, M. Pieraccini and C. Atzeni, Universal fluctuations in tropospheric radar
measurements, EPL, 89 (2010) 20006, DOI 10.1209/0295-5075/89/20006