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IntroductionIntroduction toto LIDAR (LIDAR (laserlaserradar) Remote radar) Remote SensingSensing SystemsSystems
Francesc Rocadenbosch
Remote Sensing Lab. (RSLAB)Universitat Politècnica de Catalunya
http://www.tsc.upc.eduCampus Nord, D4-016, E08034, Barcelona (SPAIN)
roca@tsc.upc.edu
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NS Introduction to LIDAR Remote Introduction to LIDAR Remote
Sensing SystemsSensing SystemsChap.1 Optical and Technological
Considerations
Francesc Rocadenbosch
Remote Sensing Lab. (RSLAB)Universitat Politècnica de Catalunya
Campus Nord, D4-016roca@tsc.upc.edu
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INTRODUCTIONINTRODUCTION
LIDAR (LIgth Detection And Ranging)Strong optical interaction between laser/atmospheric species of interest
• λ ≈ r particles, λ >> r airborne moleculesInteracting mechanisms:
• scattering by gases ( ) and particles ( )• absorption ( )
KEYS:• Highly collimated →• ΔR(spatial resolution) ≈ meters
• Δt = [seconds-minutes]
Fig. SOURCE: Measures (1992); R.M. Measures, "Laser Remote Sensing. Fundamentals and Applications". John Wiley & Sons, 1984. (Reprint de 1992, Krieger Publishing Company).
scap ,αscag ,αabsg ,α
2
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GINTRODUCTIONINTRODUCTION
MOTIVATION OF LASER PROBING: Features Associated To Optical Wavelengths
• Strong optical interaction• High directivity of radiation
!1800103 mDcmGHzf ≈⇒=λ⇒=
Dλ
≈θΔ ⇒⎭⎬⎫
⎩⎨⎧
==λ
⇒cmD
nm1532
µrad50≈θΔ
– (Comparison with RADAR) to achieve the same angular resolution at 3 GHz,
• Larger (optical) Doppler shifts than at RF wavelengths
5102≈
λλ
≈→λ
−=lidar
radarradar
d
lidardr
d ffvf
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INTRODUCTIONINTRODUCTION
HISTORICAL BACKGROUND• (1930) Searchligths• (1960) Laser invention
– Offers: High collimation, purity and spectral coherence (Δλ≈ 0.01 nm)• (1962) Fiocco & Smullin
– bounce a laser beam off the Moon. Study atmospheric turbid layers• (1963) Ligda
– Q-switching: Enables short width (τl), high-energy laser pulses– (Ep ≈ 1J, τl ≈ 10ns, PRF ≈ 10Hz)
• (1973) Semiconductor laser (GaAs)– Laser diode arrays. Trade-off between peak energy (Ep) ↓ and PRF ↑
PRFET
EE lpl
p τ=τ
=
• (2002) TLD-technologies and ps-lidar– Spectroscopic Lidar (detection of chemical species), 3D mapping
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GOPTICAL AND TECHNOLOGICAL CONSIDERATIONSOPTICAL AND TECHNOLOGICAL CONSIDERATIONS
BEER’S (or BOUGUER’S) LAWDescribes intensity of a laser beam propagating in an inhomog. medium
( ) ( ) ( )[ ]∫ λα−=λ=λ R drrRT
II
00
,exp,
• where: I0 is the intensity at r=0, I is the intensity at r=R, α is the atmospheric extinction coef., T(λ,R) is the transmissivity in (0,R) and,
SPECTRAL BANDSLidars operate in atmospheric transmission windows
• 0.4-0.7 μm (VIS), 0.7-1.5 μm (NIR), 3-5 μm y 9-13 μm (IR)• “eye-safe”: λ >1.4 μm (100 mW/cm2, 1J/cm2)• Trade-off: Laser and detector availability!
– Ej. Ruby (0.69 μm), Nd:YAG (1.064 μm), CO2 (9-10 μm), “eye-safe” 1.55μm
][ 1,,,
−++= kmabsgscapscag αααα
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OPTICAL AND TECHNOLOGICAL CONSIDERATIONSOPTICAL AND TECHNOLOGICAL CONSIDERATIONS
RAYLEIGH SCATTERING (i.e., molecular/gas scattering, r << λ)
( )⎟⎟⎠
⎞⎜⎜⎝
⎛δ−δ+
λ−π
≈βn
ng N
n76361
4
222
Theoretical classic-oscillator relationsBackscattering coefficient
Extinction coefficient
N is the molecule number densityn is the refraction indexλ is the radiation wavelengthδn is the depolarization ratio
( )g
n
ng N
nβ
π=⎟⎟
⎠
⎞⎜⎜⎝
⎛δ−δ+
⎥⎥
⎦
⎤
⎢⎢
⎣
⎡
λ−ππ
≈α3
876361
38
4
222
SEE ALSO: B.A. Bodhaine, N.B. Wood, E.G. Dutton, J.R. Slusser, “On Rayleigh Optical Depth Calculations,” J. Atmospheric and Oceanic Technology 16(11), 1854-1861 (1999).
Reminder: INTERACTION MECHANISMS
1) Rayleigh scattering (molecules, r << λ)
2) Mie scattering (aerosols, r ≈ λ)3) Others: Absorption
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GOPTICAL AND TECHNOLOGICAL CONSIDERATIONSOPTICAL AND TECHNOLOGICAL CONSIDERATIONS
RAYLEIGH SCATTERING (i.e., molecular/gas scattering, r << λ)
Reminder: INTERACTION MECHANISMS
1) Rayleigh scattering (molecules, r << λ)
2) Mie scattering (aerosols, r ≈ λ)3) Others: Absorption
( ) ( ) ( )( )zTzPzg
42234 10·6.61109154.2 −−−− λλ+×=α
SOURCE: P. Menéndez-Valdés, “Atmospheric Transmission and Climatic Effects in the Assessment of Atmospheric Losses on an Optical Link Budget.” UPC, UPM, IAC, ONERA, Final Report (A. Comerón, Ed.). ESA contract no. 8131/88/NL/DG, Barcelona, Oct. 1989.
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Lidar ratio defined as:
OPTICAL AND TECHNOLOGICAL CONSIDERATIONSOPTICAL AND TECHNOLOGICAL CONSIDERATIONS
MIE SCATTERING (i.e., aerosol/particle scattering, r ≈ λ)
SOURCE: The Infrared and Electro-Optical Systems Handbook,SPIE Press, (1993).
Mie scattering diagram• x= (2π/λ)r= 8, m=1.25+j0.0• i1 and i2 are the ⊥ and || components
( ) ( )( )RRRS aer
aer
Mλ
λ
βα
=λ,
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GOPTICAL AND TECHNOLOGICAL CONSIDERATIONSOPTICAL AND TECHNOLOGICAL CONSIDERATIONS
MIE SCATTERINGTypical extinctions and Deirmendjian’s distribution function,
( ) ( )( )1,0exp=γ∞<<−= γα
rbrarrn
Shaping parameters
N: Aerosol numberdensity
W: Aerosol weightdensity
RN, RM are themodal radii fornumber densityand mass, respectively
SOURCE: The Infrared and Electro-Optical Systems Handbook,SPIE Press, (1993).
( ) ( )drrnrQr extaer λπ=α ∫
∞λ ,0
2
Where:
And:
2rQ ext
extπσ
=
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OPTICAL AND TECHNOLOGICAL CONSIDERATIONSOPTICAL AND TECHNOLOGICAL CONSIDERATIONS
ATMOSPHERIC OPTICAL COEFFICIENTSConcerning total components note that:
( ) ( ) ( ) ( )RRRR absmolaerλλλλ α+α+α=α
≈ 0
( ) ( ) ( )RRR molaerλλλ β+β=β
Fig. SOURCE: R.T.H. Collis and P.B. Russell, “LidarMeasurement of Particles and Gases by Elastic Backscattering and Differential Absorption,” Chap.4 in Laser Monitoring of the Atmosphere, E.D. Hinkley, Ed., (Springer-Verlag, New York, 1976), pp.71-102.
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GOPTICAL AND TECHNOLOGICAL CONSIDERATIONSOPTICAL AND TECHNOLOGICAL CONSIDERATIONS
1 – 5 kmTemperature
Chemical species concentration in the atmosphere (SO2, NO, CO, H2S, C2H4, CH4, H2CO, H2O, N2,
O2 ...)
Ruby (λ =694.3, 347.2 nm)N2 (λ =337 nm)
Nd:YAG (λ =1064, 532, 355 nm)
Raman
1 – 90 km
Chemical species concentration, especially in upper atmosphere (OH, Na, K, Li, Ca Ca+), oil on water
surface, chlorophyll
DyeN2 (λ =337 nm)
NeFluorescence
1 – 5 km
Temperature, pressure
Chemical species concentration (SO2, O3, C2F4, NH3, CO, CO2, HCl, ...
Dye, CO2, excimer, parametric oscillator(OPO), Ti:Sapphire
Differentialabsorption
3-5 kmWind velocityDoppler shift in aerosol backscattered radiationNd:YAG (λ=1064 nm)Edge
technique
15 kmWind velocityDoppler shift in aerosol backscattered radiationCO2 (λ=10.6 μm)
Nd:YAG (λ=1064 nm)Tm,Ho:YAG (λ=2.1 μm)
Homodyneor
heterodyne
10–50 km
Transport, stratification,temperature in
upper atmosphere, wind velocity
Dust, clouds, smoke
Ruby (λ=694.3, 347.2 nm)Nd:YAG (λ=1064, 532,
355 nm)XeF (excimer; λ=351 nm)
Directdetection
Elas-tic
IndirectDirectRan-ge
MeasurementsLaserLidar type
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OPTICAL AND TECHNOLOGICAL CONSIDERATIONSOPTICAL AND TECHNOLOGICAL CONSIDERATIONS
LASER SOURCESBasic types: Solid state, gas, dye, semiconductor
SOURCE: R.M. Measures, Laser Remote Sensing: Fundamentals and Applications,(Krieger, Malabar, Fla., 1992), Chap.4, pp. 146-204.
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LASER SOURCES VS. WAVELENGTH
OPTICAL AND TECHNOLOGICAL CONSIDERATIONSOPTICAL AND TECHNOLOGICAL CONSIDERATIONS
SOURCE: J. Hecht,Understanding Lasers,IEEE Press.
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OPTICAL AND TECHNOLOGICAL CONSIDERATIONSOPTICAL AND TECHNOLOGICAL CONSIDERATIONS
DETECTORS vs. SPECTRAL BANDS
Fig. DETECTORS OF INTEREST IN LIDAR SCIENCE.Spectral dependence of Detectivity, D*(λ) [cm·Hz1/2W-1], for photoconductors (PC) and photodiodes (PD) of interest in LIDAR (0.3 ≤ λ ≤ 10 μm typ.) for different materials.
PMTs PIN, APD Thermal
SOURCE: R.M. Measures, Laser Remote Sensing: Fundamentals and Applications,(Krieger, Malabar, Fla., 1992), Chap. 6, pp. 205-236.
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GLIDAR CLASSIFICATION OVERVIEWLIDAR CLASSIFICATION OVERVIEW
A) Based on their APPLICATIONELASTIC-BACKSCATTER LIDAR (or “backscatter lidar”) measures...
• the average content of particulate and molecular matter (be themcontaminating or not) in the atmosphere
• winds (cross-correlation techniques) and others (range-finders, CMM, ...)
WIND LIDAR (Doppler lidar)
SPECTROSCOPIC LIDAR → measurement of chemical species
B) Based on their CONFIGURATIONMONO-STATIC LIDAR
• Types: 1) Backscatter, 2) DIAL, 3) Raman, 4) Doppler, 5) Fluorescence, 6) Others
BI-STATIC LIDAR• Types: 1) Long-path absorption
Airborne (helicopter, plane, satellite), mobile (van, truck), or ground-based.
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UPC BACKSCATTER LIDARUPC BACKSCATTER LIDAR
ΔR = 7.5 m, Δt = 1 min
LASER RECEIVER SYSTEM SPECSGain medium Nd:YAG Focal length 2 m Configuration Vertical biaxialEnergy 0.5 J/532 nm Aperture ∅ 20 cm System NEP 70 fW·Hz-1/2
Divergence 0.1mrad Detector APD (EGG C30954) Min. Det. Power < 5 nWPulse length 10 ns Net Responsivity 6×101-3×106 V/W Acquisition 20 Msps/12bitPRF 10 Hz Bandwidth 10 MHz Spatial resolution 7.5 m
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Chap.2. Elastic Chap.2. Elastic LidarLidar SystemsSystems
Francesc Rocadenbosch
Remote Sensing Lab. (RSLAB)Universitat Politècnica de Catalunya
Campus Nord, D4-016roca@tsc.upc.edu
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SUMMARYSUMMARY
• Ruby (λ = 694.3 nm, 347.2 nm)• Nd:YAG (λ = 1064, 532 nm, 355 nm)• Excimer (λ ~ 350 nm)
νhνh
GROUND LEVEL
VIRTUAL LEVEL
(b)
MEASUREMENTS:• Direct:
Aerosol/molecular composed intensity returns
• Indirect:(Usually requires calibrating conditions/hypotheses)
Optical parameters, pollution concentration and flux rate, wind
LASER TYPES:
ELASTIC INTERACTION
Types of interaction:• 1) Rayleigh scattering
(molecules, r << λ)• 2) Mie scattering
(aerosols, r ≈ λ)Types of elastic lidar:
• 1) Backscatter lidar• 2) Doppler lidar
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GAPPLICATIONSAPPLICATIONS
ENVIRONMENTAL• Pollution monitoring (source
strength and location), Fires• Transport models
– Air-quality regulations– Air-mass fluxes
• Aerosols role– Earth-atmosphere radiative budget– Photochemical effects– Air-mass tracers (e.g. wind tracers)
METEOROLOGICAL AND FSO COMMUNICATIONS
• PBL (Planetary Boundary Layer)• Cloud extent and monitoring• Estimation of atmospheric
attenuation (dB/km)
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ARCHITECTURE (I)ARCHITECTURE (I)
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GARCHITECTURE (II)ARCHITECTURE (II)
Fig. SOURCE: Measures (1992); R.M. Measures, "Laser Remote Sensing. Fundamentals and Applications". John Wiley & Sons, 1984. (Reprint de 1992, KriegerPublishing Company).
RECEIVING OPTICAL SYSTEM
• Telescope– “optical antenna”– effective area, Ar
• Inteference filter– limits background
power
• O/E converter– Photodiode, PMT– Conditioning chain
][radfrFOV d=
( ) λΩλ= ddALP rbback
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SPATIAL RESOLUTION (I)SPATIAL RESOLUTION (I)
LIDAR R
τc
τ=t
INTERACION OF A LIGHT PULSE WITH THE ATMOSPHERE
• The max range from which energy is received at time t is R0.• At the same time t, additional energy is received from ranges
illuminated by portions of the pulse transmitted after the leading edge, the min. range from which energy is received is R1.
Cell producing thebackscattered radiationarriving to the lidar at 0tt =
2)(1 τ−= otcR 200 tcR =)( τ−otc otc
Location of lightpulse at
ott =
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GSPATIAL RESOLUTION (II)SPATIAL RESOLUTION (II)
SPACE-TIME DIAGRAM(rectangular-shaped laser pulse, τL)
( )22
ddL ccR τ≈
τ+τ=Δ
2L
acR τ
=Δ
Using analog recording (τd=0),
Using a time detectionwindow of length τd=1/fs(e.g., A/D sampling, photon counting),
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THE (ELASTIC) LIDAR EQUATION (I)THE (ELASTIC) LIDAR EQUATION (I)
ΔΩ=Ar/R2
r=RΔθ
ΔR
Ar
2Δθ
R
N → Particle concentration [part/m3]dσ(π)/dΩ → Backscatter cross-section per solid-angle unit [m2/sr ]β → Backscattering coef [m2/m3sr]β = N dσ(π)/dΩ [m-1sr-1]
WITHIN THE SCATTERING VOLUME:
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GTHE (ELASTIC) LIDAR EQUATION (II)THE (ELASTIC) LIDAR EQUATION (II)
BASIC INTERVENING MAGNITUDES1) Laser emitted power per pulse (tL), P0 [W ]
2) Incident power density on the atmospheric resolution cell, Ein [W/m2]
3) Cell-backscattered power per solid-angle unit, Ksca [W/sr]
4) Backscattered power collected by the telescope, P(R) [W]
L
EPτ
=0
( ) [ ] θΔ=∫ α−π
= Rrduur
PRE Rin ,)(exp 02
0
( ) ( ) ( )⎩⎨⎧
τ=ΔΔπ=
β=2
2
Linsca cR
RrVwithVRERRK
( ) ( ) [ ] 20 ,)(expRAdxxRKRP rR
sca =ΔΩ∫ α−ΔΩ=
( ) ( ) ( )[ ]∫ α−β= Rrc
duuRR
AERP 02
2 2exp
5) Finally,
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THE (ELASTIC) LIDAR EQUATION (III)THE (ELASTIC) LIDAR EQUATION (III)
( ) ( ) ( )[ ] ( )RdrrRRKRP
Rξλα−λβ=λ ∫02 ,2exp,,
Elastic LIDAR Equation (simple scattering)
where:
rAEcK2
=
( ) ( ) ( ) ,,Ω
=d
dRNR πσλβ
where: (peak) energy [J]effective telescope area [m2]
E
rA
( ) 10 ≤ξ≤ R
atmospheric optical extinction coef. [m-1]atmospheric optical backscatter coef. [m-1sr-1]
– where
– N is the average density of aerosols + molecules [m2/m3sr]
overlap factor [ ], optical return power [W]system constant [W m3 ],
( )R,λα
( )R,λβ
( )Rξ
( )RP
K
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GTHE LIDAR EQUATION (IV)THE LIDAR EQUATION (IV)
ATMOSPHERIC OPTICAL COEFFICIENTS
Concerning the lidar Eq., note that:
( ) ( ) ( ) ( )RRRR absmolaerλλλλ α+α+α=α
≈ 0
( ) ( ) ( )RRR molaerλλλ β+β=β
Fig. SOURCE: R.T.H. Collis and P.B. Russell, “LidarMeasurement of Particles and Gases by Elastic Backscattering and Differential Absorption,” Chap.4 in Laser Monitoring of the Atmosphere, E.D. Hinkley, Ed., (Springer-Verlag, New York, 1976), pp.71-102.
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THE LIDAR EQUATION (V)THE LIDAR EQUATION (V)
FURTHER COMMENTS:
1) Assuming a homogeneous atmosphere and ideality systemconditions, the lidar equation takes its simplest form:
( )RRK= P(R) α−β 2exp2
transmittancebackscatter
2) Note the LIDAR optical thickness (COT) and related transmissivity!
( )[ ] ( ) r)dr(RCOTRCOTR)T(R
0,;2exp, λα=−=λ ∫
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GTHE LIDAR EQUATION (VI)THE LIDAR EQUATION (VI)
OPTICAL OVERLAP FACTOR (OVF)
The telescope cannot “read” the full atmospheric cross-section illuminated by the laser beam (i.e., does not lie within its FOV)
It is a function of many geometrical and optical parameters of both the laser and telescope.
Fig. SOURCE: Measures (1992).
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THE LIDAR EQUATION (VII)THE LIDAR EQUATION (VII)
[ ]R d R + W Rf = y o
222oi δθ −+±−
[ ] ( )[ ]443442143421
positionysizei Rf f = y
−
−Ω−±− δθ
[ ] ( )[ ]4434421
43421 positionysize
i R f W Rf = y
−
−Ω−±− δ0
Atmospheric laser foot-print imaged is (telesc. far-field):
A)
B)
azimuth adj. elevation adj.
OVF OPTICAL ALIGNMENTOVF OPTICAL ALIGNMENT
8
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GTHE LIDAR EQUATION (VIII)THE LIDAR EQUATION (VIII)
1
2
3
4 OK
REF
brightest area
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THE LIDAR EQ. (IX): BASIC INVERSIONSTHE LIDAR EQ. (IX): BASIC INVERSIONS
RANGE CORRECTION (R2P):Backscatter-transmittance plotReveals atmospheric structure
• Mixing aerosol layer• Cloud structure
CEILOMETRY:Cloud-height extent monitoring
• Cloud base, peak, top• No. of layers
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GTHE LIDAR EQ. THE LIDAR EQ. (X): BASIC INVERSIONS(X): BASIC INVERSIONS
LOS: 15-DEGZ
LOS: 15-DEGZ
• For optically “clear” atmospheres, the “range-corrected” (R2P), “backscatter” and “extinction” representations look very much alike.
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SIGNAL CONDITIONING (I): RECEIV. CHAINSIGNAL CONDITIONING (I): RECEIV. CHAIN
R’V: Net Voltage Responsivity (V/W)Vos: Total system offset (user+drift+background)ntot: Total noise (photodetection + electronic)εq: Quantization noisexa,s: A/Synchronous interferences
R’V Ideal ADC
ntot Vos εq xa+xs
V(R)P(R)
∑+++′= Δtdt
dVVVPRV driftuserdriftBackvOS
unwanted terms
Sampling at fs, detection time τd=1/fs, so that
s
d
fccR
22=
τ≈Δ
)()()()( RxRxnVRLPRRV saqtotosv ++ε+++=
10
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GEXAMPLE OF GOOD SIGNAL CONDITIONINGEXAMPLE OF GOOD SIGNAL CONDITIONING
0 5 10 15-0.2
00.20.40.60.8
11.21.4
Vout. File: o4100110. #Packets: 1. #IP/shot: 1000. Rmin: 0
R [km]10 10.5 11 11.5
01234567
x 10-3
R [km]
0 5 10 150
0.10.20.30.40.50.60.70.8
R [km]13 13.5 14 14.5 15
2.5
3
3.5
4
4.5
x 10-4
R [km]
R·P
(R) [
W·k
m]
22
V(R
) [V
]
V(R
) [V]
V(R
) [V]
(a)
(b)
(c)
(d)
inset (d)
inset (c)
εq
1 0 0 0
εq
1 0 0 0
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EXAMPLE OF BAD SIGNAL CONDITIONINGEXAMPLE OF BAD SIGNAL CONDITIONING
0 2 4 6 8 100
0.5
1
1.5
2
Vout. File: d7091951. #Packets: 1. #IP/shot: 500. Rmin: 0
R [km]8 8.5 9 9.5 10
-2
0
2
4
6
x 10-5
R [km]
0 2 4 6 8 10-0.02
0
0.02
0.04
0.06
0.08
0.1
R [km]8.5 9 9.5
-1
0
1
2
3
4
5
x 10-3
R [km]
R·P
(R) [
W·k
m]
22
R·P
(R) [
W·k
m]
22
V(R
) [V]
V(R
) [V
]
(e)
(f)
(g)
(h)
inset (d)
inset (c) εq
5 0 0
wrong V( )correction
∞
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GSIGNALSIGNAL--TOTO--NOISE NOISE RATIORATIO
DEFINITION
( ) ( )( )
[ ][ ]VV
BRRLPR
voltagenoisevoltageusefulRSNR
V
VV ,21σ
==
NOISE SOURCES
⎥⎦
⎤⎢⎣
⎡σ+σ+σ=σ
HzV
thdshsshV
222
,2
,2
where (...):
photo-induced (i.e., signal-induced) shot noise
dark-shot noise
thermal noise
( ) ( )[ ]LPRPRFMqGR backioTssh +=σ 222, 2
( )dbdsTdsh IFMIqG 222, 2 +=σ
22,
2Tithth Gσ=σ
OPERATION MODES• sh,s dominant, • th dominant,( ) 21RPSNR ∝ ( )RPSNR ∝
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SPACE LIDARSPACE LIDAR
NASA, Lidar In-space Technology Experiment (LITE)
SPECS: Elastic lidar, Nd:YAG (1064, 532, 355 nm), Discovery 1994.APLIC: Clouds & statosphere aerosol density, temperature
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GSPACE LIDARSPACE LIDAR
LITE (Lidar In-space Technology Experiment)
SOURCE: http://www-lite.larc.nasa.gov/
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SPACE LIDARSPACE LIDAR
OTHER PROJECTS• ATLID (from ESA): Similar to LITE (NASA)• ALADIN (from ESA): Wind lidar space-borne sensor• CALIPSO (from NASA-CNES): Aerosol and clouds• ADM-AEOLUS: Wind sensing
13
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GEXAMPLES: MICROEXAMPLES: MICRO--LIDARLIDAR
CLOUD AND AEROSOL M-LIDAR
MAIN FEATURES:• Self-alignment of emission and
reception axes• Eye-safe• Compact and portable
SOURCE: CIMEL Electronique, http://www.cimel.fr (Mod. CE370-2)
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EXAMPLES: BACKSCATTER LIDAR EXAMPLES: BACKSCATTER LIDAR -- UPC 1996UPC 1996
LASER RECEIVER SYSTEM SPECSGain medium Nd:YAG Focal length 2 m Configuration Vertical biaxialEnergy 0.5 J/532 nm Aperture ∅ 20 cm System NEP 70 fW·Hz-1/2
Divergence 0.1mrad Detector APD (EGG C30954) Min. Det. Power < 5 nWPulse length 10 ns Net Responsivity 6×101-3×106 V/W Acquisition 20 Msps/12bitPRF 10 Hz Bandwidth 10 MHz Spatial resolution 7.5 m
DISTINCTIVE SPECS:(as compared to μW RADARS)
ΔR = 7.5 m!Δt = 1 min
14
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GEXAMPLES: BACKSCATTER LIDAR EXAMPLES: BACKSCATTER LIDAR -- UPC 1996UPC 1996
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ADVANCED CONFIGURATIONS: SRL ADVANCED CONFIGURATIONS: SRL -- UPC 2004UPC 2004
Alig
nmen
tP
olar
im. S
ubs.
(R)
Polarim. Subs. (T)
Fig. 1 Fig. 2
Fig. 3
15
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GADVANCED CONFIGURATIONS: SRL ADVANCED CONFIGURATIONS: SRL -- UPC 2004UPC 2004
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PSEUDOPSEUDO--RANDOM SYSTEMSRANDOM SYSTEMS
PN SEQUENCES (I) KEYS:1) A feedback n-stage shift register with non-zero initial state acts as a periodic seq. generator.
2) The PN (pseudo-noise) sequence length is
i.e., period = NTb
3) Usually, the binary polar NRZ sequence is used,
12 −= nN
12 −=′ kk aa
Fig. SOURCE: Takeuchi et al, “Random modulation CW lidar”, Appl. Opt., 22(9), 1382-6 (1983).
( ) ( ) ⎟⎟⎠
⎞⎜⎜⎝
⎛ −Π−=′ ∑
b
b
kk T
kTtata 12
ka
ka
16
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GPSEUDOPSEUDO--RANDOM SYSTEMSRANDOM SYSTEMS
PN SEQUENCES (II)4) Periodic Autocorrelation
( )⎩⎨⎧
≠==
=+
′ 000~ 2
1
jj
nR Nl
NN
aa
5) Reencounters the system (atmospheric) impulse response →
• System identification• Demodulation is
substituted by correlation
( ) ( ) ( ) ( )RRTRR
Actg r ξλξβ= 22
12
)(
( ) ( ) ( )( ) ( ) ( )⎩
⎨⎧
∗=
′==tgtxty
taTPtEatx b~~
~0
( ) ( ) ( ) ( )tgtatytg ≈′∗= ~~̂
( )⎩⎨⎧
≠−=
=′′ 001~
1 jj
jRN
aa
( )2
,11 b
baa
NTNTN
NR ≤τ−⎟⎟⎠
⎞⎜⎜⎝
⎛ τΛ
+=τ′′
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PSEUDOPSEUDO--RANDOM SYSTEMSRANDOM SYSTEMS
Fig. SOURCE: Bundschuh et al., “Feasibility study of a compact low cost correlation LIDAR using a pseudo-noise modulated diode laser and anAPD in the current mode”, IEEE (1996).
THE ATMOSPHERIC ID. PROBLEM• The impulse excitation is substituted by
SYSTEM LAYOUT
( ) ( )tEltR~ bss δ=
17
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GPSEUDOPSEUDO--RANDOM SYSTEMSRANDOM SYSTEMS
Fig. SOURCE: Takeuchi et al, “Diode-laser random-modulation CW lidar”, Appl. Opt., 25(1), 63-7 (1986).
PROTOTYPE EXAMPLE
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Chap.3. Raman SystemsChap.3. Raman Systems
Francesc Rocadenbosch
Remote Sensing Lab. (RSLAB)Universitat Politècnica de Catalunya
Campus Nord, D4-016roca@tsc.upc.edu
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RAMAN LIDAR SUMMARYRAMAN LIDAR SUMMARY
OPERATIONAL PRINCIPLE1) In contrast to elastic systems, the return wavelength, λR, is shifted from the incident one, λ0.2) Wavelength shift, κ, depends oneach molecular species.
3) Very faint returns.• requires photon counting• very often, night-time operation
0
0
1 κλ−λ
=λR
Fig. ADAPTED FROM: Inaba, H. Detection of Atoms and Molecules by Raman Scattering and Resonance Fluorescence. In Laser Monitoring of the Atmosphere, Hinkley, E. D., Ed.; Springer-Verlag: New York, 1976; Chap. 5, 153-236.
2
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GRAMAN LIDAR SUMMARYRAMAN LIDAR SUMMARY
APLICATIONS1) Self-calibrated lidar (N2 shift)
• Absolute concentration of anyatmospheric species can be determined by comparison to theN2-atmospheric return
2) Temperature profiler (±2K)
3) Spectroscopic sensing (COMPARISON WITH DIAL) • Low detection sensitivity at long ranges due to the low Raman cross
sections that ...• limit the method to the detection of species present in high concentrations
(e.g. smoke stacks in industrial plants, 100-1000 ppm, 30-100 m).• In contrast, measurements are always range resolved (RR) and there is no
need to tune the laser in absorption bands.
Fig. SOURCE: Measures (1992).
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RAMAN LIDARRAMAN LIDAR
MEASUREMENTS:• Direct: Concentration of chemical
species in the atmosphere suchas
SO2, NO, CO, H2S, C2H4, CH4, H2CO, H2O, N2, O2...
• Indirect: Temperature, Humidity, α, β, SM
LASER TYPES:• Ruby (λ = 694.3 nm, 347.2 nm)• N2 (λ = 337 nm)• Nd:YAG (λ = 1060 nm, 532 nm, 266 nm)• Excimer (λ ~ 350 nm)
νh*νh
GROUND LEVEL
VIRTUAL LEVEL
VIBRATIONALLYEXCITED LEVEL
INELASTIC INTERACTION
3
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GRAMAN LIDARRAMAN LIDAR
The Raman shift, κ:
1) does not dependon the excitationwavelength λ0 and,
2) it is specific of thechemical species
A) Laser needs not be tunable
B) The Ramanspectrum ischaracteristic of eachmolecule
C) Conveystemperature info.
Overview of the lidar backscatter signals for 532-nm laser excitation wavelength.
RAMAN SPECTRUM CHARACTERISTICS
Fig. SOURCE: Behrendt, A., et al., “Combined Raman lidar for the measurement of atmospheric temperature, water vapor, particle extinction coefficient, and particle backscatter coefficient”, Appl. Opt. 41 (36), 7657-7666, (2002).
Stokes linesAnti-Stokes
Rayleigh and Mie Scattering
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RAMAN LIDARRAMAN LIDAR
Fig. SOURCE: Inaba, H. Detection of Atoms and Molecules by Raman Scattering and Resonance Fluorescence. In Laser Monitoring of the Atmosphere, Hinkley, E. D., Ed.; Springer-Verlag: New York, 1976; Chap. 5, p.162.
[ ]1
0Rcm,11 −κκ−
λ=
λ
KEY CONCEPTS1) Raman components
• Stokes lines– molecule gains energy from the
radiation field– scattered radiation is at λR> λ0
• Anti-Stokes lines (λR<λ0)
2) Motivation for the “wavenumber”concept (with κ, the Raman shift):
3) Raman cross-sections• dependency ∝ λ-4
Common Raman shifts:N 2 2 3 3 1 cm -1 H 2O 3 6 5 4 cm -1
O 2 1 5 5 6 cm -1
( ) ( )Ray
4,3
Raman dd10
dd
Ωπσ
≈Ωπσ −−
4
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GRAMAN LIDAR LINKRAMAN LIDAR LINK--BUDGETBUDGET
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TEMPERATURE MEASUREMENT (I)TEMPERATURE MEASUREMENT (I)
Fig. SOURCE: Inaba, H. Detection of Atoms and Molecules by Raman Scattering and Resonance Fluorescence. In Laser Monitoring of the Atmosphere, Hinkley, E. D., Ed.; Springer-Verlag: New York, 1976; Chap. 5, 153-236.
KEYRaman signatures are direct measures of the relative populations among the internal molecular modes
• (In termal equilibrium) →fundamental def. of temperature
METHODS1) Rotational Raman (RR)
• Comparison of the envelope shape of all the lines
• Intensity ratio of selected spectral regions of the band
Suitable for atmospheric profiling
2) Vibrational Raman (VR)• +• Intensity ratio between Stokes
and anti-Stokes components• Width of a specific Q-branch
Suitable for high-temperature diagnostics (e.g. flames)
5
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GTEMPERATURE MEASUREMENT (IITEMPERATURE MEASUREMENT (II))
Fig. SOURCE: Behrendt, A., et al., “Combined Raman lidar for the measurement of atmospheric temperature, water vapor, particle extinction coefficient, and particle backscatter coefficient”, Appl. Opt. 41 (36), 7657-7666, (2002).
RASC (GKSS) lidar1) T (temperature)2) WV (water vapor mixing ratio)3) α, β, SM
4) RH (humidity)
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UPC POLYCROMATOR TEST LAYOUTUPC POLYCROMATOR TEST LAYOUTH
6
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GTEMPERATURE MEASUREMENT (III)TEMPERATURE MEASUREMENT (III)
Tab. SOURCE: Behrendt, A., et al., “Combined Raman lidar for the measurement of atmospheric temperature, water vapor, particle extinction coefficient, and particle backscatter coefficient”, Appl. Opt.41 (36), 7657-7666, (2002).
DISCUSSION PARAMETERS (RASC lidar LAYOUT)
Note:ND filters are used to cope with saturation effects in the RR channels in the lower troposfere (correction of photon-counter receiver dead-time effects).
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TEMPERATURE MEASUREMENT (IV)TEMPERATURE MEASUREMENT (IV)
Fig. SOURCE: Behrendt, A., et al., “Combined Raman lidar for the measurement of atmospheric temperature, water vapor, particle extinction coefficient, and particle backscatter coefficient”, Appl. Opt.41 (36), 7657-7666, (2002).
Specific RR Temperature approaches:
Use of two RR channels with opposite temperature dependency
• + 3rd RR channel (isosbestic point) as reference or,
• combine them to obtain a temperature-indep. reference
• calibrate Q(T) with a radiosonde– find c for minimum temp. variation
( ) ( )( )
( ) ( ) ( )zcNzNzNTNTNTQ
RRRRref
RR
RR
21
1
2
+=
=
7
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GTEMPERATURE MEASUREMENT (V)TEMPERATURE MEASUREMENT (V)
Fig. SOURCE: Behrendt, A., et al., “Combined Raman lidar for the measurement of atmospheric temperature, water vapor, particle extinction coefficient, and particle backscatter coefficient”, Appl. Opt. 41 (36), 7657-7666, (2002).
Problem: Elastic cross-talk with the RR channelAction: Calibrate on a cirrus cloud using
( ) ( )( ) ( )zNTN
TNTQElRR
RR
ε−=
1
2
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MOLECULAR SPECIES (GAS) DETECTION (I)MOLECULAR SPECIES (GAS) DETECTION (I)
CONCEPTS:1) The absolute concentration of each molecular species can be performed by comparing the Raman backscattered intensity with that of the Raman line from N2 which occupy the same volume.
( ) ( ) ( ) ( ) ( ) ( ) ( )[ ]{ }∫ ξξα+ξα−×⎥⎦
⎤⎢⎣
⎡Ωπσ
λΔ=λλ
λλλ
R tottotRRR d
dd
RNTFR
ROKRPR
RRR 02 0
exp,
1A) Raman-backscattered signal:
1B) (Oversimplified) Gas-to-N2 normalised ratio
( )( )
( )( )
( )( )
( )( )
( )( )
( )( ) ( )
( ) ( ) ( )[ ]{ }∫ ξξα−ξα−=λλτΔ
λλτΔλξλξ
⎥⎥⎦
⎤
⎢⎢⎣
⎡
ΩπσΩπσ
λΔλΔ
=
λλ
λ
λ
λ
λ
R tottotNX
NXN
X
N
X
NN
XX
N
X
dRwhere
Rdddd
RNRN
TFTF
RORO
RPRP
NX
N
X
N
X
0exp,,
,,,,,
N2-normalised cross section
solve for Nx(R) known (US-std model, radiosonde)
8
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GMOLECULAR SPECIES (GAS) DETECTION (II)MOLECULAR SPECIES (GAS) DETECTION (II)
2) The (VR) spectrum is preferred to the (RR)
• RR lines of major atmospheric constituents overlap,
• large Rayleigh-Miecross-talk.
• In contrast, VR cross-sections are usually lower than RR ones.
1C) (Estimation of the) Differential Transmission term:• Molecular extinction → US-std. atmosphere model + radiosonde• Aerosol extinction → Cooperative elastic-Raman channel (N2)
– Only in hazy conditions (See Elastic-Raman inversion Sect. in Chap.7)• Angström coefficient → E.g. Sun-photometer calibration
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MOLECULAR SPECIES (GAS) DETECTION (III)MOLECULAR SPECIES (GAS) DETECTION (III)
SOME MEASUREMENT EXAMPLES
• Fig.1 Raman spectroscopy from the ordinary atmosphere
• Fig.2 Molecular species in an oil smoke plume
Fig.1
Fig.2
Fig. SOURCE: Inaba and Kobayasi, Opto-Electron 4, 101 (1972).
9
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GWATERWATER--VAPOR MEASUREMENT (I)VAPOR MEASUREMENT (I)
WATER-VAPOR (WV) KEYS:• Influences convective stability (likelihood of storm initiation)• Most active green-house gas
– it absorbs terrestrial radiation more strongly than does CO2
• Water-vapor mixing ratio (w)
– where MWx stands for molecular weight (≈ 18g/mol for H2O and ≈ 28.94 g/mol for dry air) and Nx stands for molecule number concentration.
• Importance of the mixing ratio:– It is conserved in atmospheric processes that do not involve condensation or
evaporation– Serves well as a tracer of the movement of air parcels in the atmosphere
( )( )
( )( )
( )( )RN
RNRN
RNMWMW
RNRN
MWMW
wN
OH
N
OH
DryAir
OH
DryAir
OH
DryAir
OH
2
2
2
2222 485.078.0/
≈≈=
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WATERWATER--VAPOR MEASUREMENT (II)VAPOR MEASUREMENT (II)
DERIVATION FROM THE RAMAN CHANNELSFrom Eq.(1B) in Slide 14
( )( )
( )( )
( )( )
( )( )
( )( )
( )( ) ( )R
dddd
RNRN
TFTF
RORO
RPRP
NHN
H
N
H
RN
RH
N
H
N
H
N
H ,,,,
λλτΔλξλξ
⎥⎥⎦
⎤
⎢⎢⎣
⎡
ΩπσΩπσ
λΔλΔ
=λ
λ
λ
λ
and the definition of the mixing ratio (w)
( )( )
( )( )
( )( )
( )( )
( )( ) ( )RRPRP
TFTF
dddd
ROROw HN
N
H
HH
NN
H
N
H
N
H
N ,,,,485,0 λλτΔλΔλΔ
λξλξ
⎥⎥⎦
⎤
⎢⎢⎣
⎡
Ωπσ
Ωπσ=
λ
λ
System’s calibration factor, k*(R)
Temperature-dependent ratio
Measurement factor
– where Px(R) are background-substracted quantities.
In summary,
( ) ( )( ) ( ) ( ) ( )
( )RPRPRRRR
TFTFRkw
N
HwHNw
HH
NNL =λλτΔ
λΔλΔ
= ,,,,*
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GWATERWATER--VAPOR MEASUREMENT (III)VAPOR MEASUREMENT (III)
kappa lambdaR (1) lambdaR (2)SPECIES (cm-1) (nm) (nm)
Air 0 354,7 532,1O2 1556 375,4 580,1N2 2331 386,7 607,4H2O 3654 407,5 660,5
Excitation wavelength (lambda0)(1) 354,7 nm (Nd:YAG, THG)(2) 532,1 nm (Nd:YAG, SHG)
Cross sections are computed assuming a λ-4
dependency(i.e. higher in the UV than in the NIR)
( ) ( )( )
( )( ) ( )RRPRP
TFTFRkw HN
N
H
HH
NN ,,,,*
355 λλτΔλΔλΔ
=
EXAMPLE• In the UV (λL=355 nm), Raman channels: λN=387 nm, λH=408 nm
( )( )
( )( )H
N
H
N
ROROk
λξλξ
≈ 22.0*355
Water-Vapor Mixing Ratio Error
( )( )RPRPR
RRkw N
Hw
w
R
w
Rkw ww =σ
≈τΔ
σ+
σ+
σ=
σ τΔ ;2
2
2
2
2
2
2*
2
2
2*
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WATERWATER--VAPOR MEASUREMENT (IV)VAPOR MEASUREMENT (IV)
ERROR SOURCES AND UNCERTAINTIES• Water-Vapor Mixing Ratio Error
• k*: Calibration factor → Can be considered to be small– Calibrated using a radiosonde (e.g. VAISALA RS80-A) or a MW radiometer
• Rw: Signal-induced statistical error dominates the error budget
• = Differential Transmission (DT).– λN and λH experience different amounts of attenuation on their return trips,
caused mainly by Rayleigh scattering. The DT can be calibrated by using1) A radiosonde estimate the molecular number density (i.e, T(z), P(z))2) For hazy atmospheres (DT < 0.9 for τPBL > 2), the N2-Raman channel is
used to estimate the aerosol extinction (typ., λ-1 dependence)See Sec. Inversion of Optical Parameters / Extinction inversion,Note: WV absorbs weakly at λH=660 nm ⇒ λL=355 nm preferred to 532 nm
( )( )RPRPR
RRkw N
Hw
w
R
w
Rkw ww =σ
≈τΔ
σ+
σ+
σ=
σ τΔ ;2
2
2
2
2
2
2*
2
2
2*
aeraerNH λλ αα ,
( )RHN ,,λλτΔ
Fig. SOURCE: Inaba, H. Detection of Atoms and Molecules by Raman Scattering and Resonance Fluorescence. In Laser Monitoring of the Atmosphere, Hinkley, E. D., Ed.; Springer-Verlag: New York, 1976; Chap. 5, p.162.
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GWATERWATER--VAPOR MEASUREMENT (V)VAPOR MEASUREMENT (V)
Fig. SOURCE: Goldsmith, J.E.M., et al., “Turn-key Raman lidar for profiling atmospheric water vapor, clouds, and aerosols”, Appl. Opt.27 (21), 4979-4990, (1998).
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RELATIVE HUMIDITY MEASUREMENTRELATIVE HUMIDITY MEASUREMENT
KEY• Water-vapor mixing ratio (wH2O) + Temperature profile ⇒ RH• Derivation of the RH profile emerges from specific physical refs.1,2
( ) ( )( )zezezRH
w
=
( ) ( ) ( )( ) ( ) ( )[ ]
( )[ ]⎭⎬⎫
⎩⎨⎧
−+−
=+
=273
273exp107.6,622.0
2
2
zTMzTMze
zwzwzP
zeB
Aw
OH
OH
where e(z) is the WV pressure, and ew(z) is the saturation pressure,
– MA=17.84, 17.08 and MB=245.4, 234.2 for T < and > 273 K, respectively.
REFERENCES:1) R.R. Rogers and M.K. Yau, A Short Course in Cloud Physics (Pergamon, New York ,1988).2) R.J. List, ed., Smithsonian Meteorological Tables (Smithsonian Institution, Washington, D.C., 1951).
12
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GA COMPLETE RAMAN SYSTEMA COMPLETE RAMAN SYSTEM
Fig. SOURCE: Matthis, I, Ansmann, A et al., “Relative-humidity profiling in the troposphere with a Raman lidar”, Appl. Opt. 41 (30), 6451-6462, (2002).
LAYOUT
• 3 unshifted returns (1064, 532, 355 nm), NO polarization• 4 returns (Stokes and anti-Stokes portions) of the N2 RR spectrum• 3 vibrational Raman returns (N2 at 387, 607 nm and H2O at 407 nm)• 2 returns from the parallel and cross-polarized unshifted 532 nm
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A COMPLETE RAMAN SYSTEMA COMPLETE RAMAN SYSTEM
Fig. SOURCE: Matthis, I, Ansmann, A et al., “Relative-humidity profiling in the troposphere with a Raman lidar”, Appl. Opt. 41 (30), 6451-6462, (2002).
COMPOSITE OUTPUTS
Radiosounding calibration
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GINVERSION OF OPTICAL PARAMETERS (I)INVERSION OF OPTICAL PARAMETERS (I)
PRINCIPLE1) Two receiving channels: Besides the ELASTIC receiver, which is onlysensitive to the elastic return, another receiver -i.e., the RAMAN receiver-is spectrally tuned to the Raman-shifted wavelength (Q-branch) of anyabundant species of known relative concentration (usually N2).
2) From:• radiosoundings or• ground-level measurements of pressure and temperature +
assumption of a standard atmosphere,the N2 concentration -as a function of the range to the lidar- is inferred.
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INVERSION OF OPTICAL PARAMETERS (II)INVERSION OF OPTICAL PARAMETERS (II)
( ) ( ) ( ) ( ) ( ) ( ) ( ) ( )[ ]{ }∫ ξξα+ξα+ξα+ξα−×⎥⎦
⎤⎢⎣
⎡Ω
πσ=
λλλλ
λλλ
z aermolaermolR d
dd
zNz
zOKzPRR
RRR 02 00
exp
Raman-backscattered signal:
( )
( )( )
( ) ( )
k
R
molmolR
aer
zzzzP
zNdzd
zR
R
⎟⎟⎠
⎞⎜⎜⎝
⎛λλ
+
α−α−⎥⎥⎦
⎤
⎢⎢⎣
⎡
=αλλ
λ
λ
0
2
1
ln0
0
INVERTED ATMOSPHERIC OPTICAL PARAMETERS
Scattering wavelength dependency: λ-κ
κ−
⎟⎟⎠
⎞⎜⎜⎝
⎛λλ
=α
α
λ
λ
Raer
aer
R
00
Raman-channel inverted extinction:
14
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GINVERSION OF OPTICAL PARAMETERS (III)INVERSION OF OPTICAL PARAMETERS (III)
( ) ( ) ( ) ( ) ( ) ( ) ( )( ) ( ) ( )
( ) ( )[ ]{ }( ) ( )[ ]{ } 0
00
000
;exp
exp
0 00
0
0
00000
zzd
d
zNzPzPzNzPzP
zzzz
zz
molaer
zz
molaer
R
R
RR
R
Rmolaermolaer
≥ξξα+ξα−
ξξα+ξα−×
××⎥⎦⎤
⎢⎣⎡ β+β+β−=β
∫
∫
λλ
λλ
λλ
λλλλλλ
( )( )zz
zS aer
aeraer
0
0
0)(
λ
λλ β
α=
Backscatter inversion requires:• combination of lidar returns from both elastic and Raman channels
( ) {
⎥⎥⎥⎥
⎦
⎤
⎢⎢⎢⎢
⎣
⎡
α=β λλλλ
.
,,,,,000
compRayleigh
Raer
returnschannel
TPNPPfRR
aer
43421( ) ( ) ( ) ( )⎥⎦
⎤⎢⎣⎡ β+β→β>>β
λλλλ 0000 0000RRRR
molaeraermol
• a backscatter calibration at some height R0 so that
The lidar ratio is found as
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4. INVERTED OPTICAL PARAMETERS4. INVERTED OPTICAL PARAMETERS
0 1 2 3 4 5 672.8
73
73.2
73.4
73.6
73.8
Range [km]
ln(N
/[R2 ·z
(R)])
[a.u
.]
0 1 2 3 4 5 6-0.5
-0.3
-0.1
0.1
0.3
0.5
d/dR
[ ln(
.) ] [
a.u.
]
∑
∑=
2
2
1ˆ
i
i
iS
S
σ
σ
ML estim ML estim
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Chap.4. Wind Chap.4. Wind LidarLidar SystemsSystems
Francesc Rocadenbosch
Remote Sensing Lab. (RSLAB)Universitat Politècnica de Catalunya
Campus Nord, D4-016roca@tsc.upc.edu
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MEASUREMENT TECHNIQUES:• Coherent Doppler lidar
Along-path, focused, VAD scanning• Direct-Detection Doppler lidar
Edge-Technique (ET), Double-Edge Technique (DET), Fringe Technnique
• Spatial correlationElastic lidar (Doppler effect not used!)
LASER TYPES:• CO2 (λ = 9-10 μm)
• Up to 1 J, stability, less turbulence losses• Foreman/Huffaker (1964)
• Tm,Ho:YAG (λ = 2.1 μm)• Solid-state, eye-safe laser, some 50 mJ• Henderson&Hale (1989) [2]
• Nd:YAG (SHG, λ = 532 nm)• Roux (1994) [4]
WIND LIDAR SUMMARYWIND LIDAR SUMMARY
TRENDS:• 1-10-mJ energy• 1-10-kHz PRF• Solid-state, eye-safe technology• Co-operative Doppler radar wind profilers
[1] Clifford, S. T.; Kaimal, J. C.; Lataitis, R. J.; Strauch, R. G. Ground-Based Remote Profiling in Atmospheric Studies: An Overview. Proc. IEEE 1994, 82 (3), 313-355.
[2] Henderson, S. W.; Hale, C. P. Tunable single-longitudinal-mode diode laser-pumped Tm,Ho:YAGlaser. Appl. Opt. 1991, 29 (12), 1716-1718.
[3] Huffaker, R. M.; Hardesty, R. M. Remote Sensing of Atmospheric Wind Velocities Using Solid-State and CO2 Coherent Laser Systems. Proc. IEEE 1996, 84 (2), 181-204.
[4] Roux, R. Cooperative ventures monitor atmospheric conditions. Laser Focus World 1994, 30 (8), S7-S9.
2
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GWIND LIDAR SUMMARYWIND LIDAR SUMMARY
Uses airborne particles&molecules as “tracers” along with –usually- the Doppler principle to invert the wind radial component
• (1992) First commercial system. Specs.: 30-3000 m range, 1-m/s resolution, 150-m spatial resolution and 5-min integration time.
• (Today) Wind sensors: LAWS (NASA) and ALADIN (ESA), ...(NOAA).• A few systems rely on correlation techniques instead
λ−= r
dvf 2
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COHERENT DOPPLER LIDARCOHERENT DOPPLER LIDAR
KEYS:• Coherent Detection
– Optical heterodyne detection• Doppler broadening
– Aerosol and molecular motioninside the scattering volume
– Rayleigh and Mie peaks
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GCOHERENT DOPPLER LIDARCOHERENT DOPPLER LIDAR
DESIGN POINTS OF CONCERN:1. Photomixer efficiency requires:
• Precise alignment between local oscillator and return signalbeams– Tool: BPLO (back-propagated
oscilator)• Diffraction-limited optics• Emission laser with good phase
coherence– Longitudinal-mode operation– Long pulses (large coherence
length)• Return signal spot must be
coherent across most of itstransversal section– Van Cittert-Zernicke theorem
2. Refractive turbulence effects• Phase and amplitude distortion• Degrades signal coherence
SOURCE: With contributions from A. Rodríguez and A. Belmonte (UPC)
FIG: SOURCE: B. J. Rye and R. G. Frehlich, "Optimal truncation and optical efficiency of an apertured coherent lidar focused on an incoherent backscatter target," Appl. Opt. 31, 2891- (1992).
Assume the target area is illuminated from both thetransmitter and the BPLO (“Feuilleté model”)
ReceivingArea (Ar)
dΩrA
d2λ
≈Ω
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COHERENT DOPPLER LIDARCOHERENT DOPPLER LIDAR
ad
sc
λ≈
θλ
=ρ 61.022.1
1.22 0.61cs
da
λ λρθ
≈ =
SOURCE: With contributions from A. Rodríguez and A. Belmonte (UPC)
DESIGN POINTS OF CONCERN:1. Photomixer efficiency requires:
• Precise alignment between local oscillator and return signalbeams– Tool: BPLO (back-propagated
oscilator)• Diffraction-limited optics• Emission laser with good phase
coherence– Longitudinal-mode operation– Long pulses (large coherence
length)• Return signal spot must be
coherent across most of itstransversal section– Van Cittert-Zernicke theorem
2. Refractive turbulence effects• Phase and amplitude distortion• Degrades signal coherence
Incoherently illuminated pinholeSpatially coherent radiation is obtained within radius ρ,
The coherent transverse radius of a backscattered signal spot from a roughtarget illuminated by a Gaussian beam ofdiameter D=2a is
DR
cλ
=ρ
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GCOHERENT DOPPLER LIDARCOHERENT DOPPLER LIDAR
Turbulence/Amplitude effects
Turbulence/Phase effects
SOURCE: With contributions from A. Rodríguez and A. Belmonte (UPC)
DESIGN POINTS OF CONCERN:1. Photomixer efficiency requires:
• Precise alignment between local oscillator and return signalbeams– Tool: BPLO (back-propagated
oscilator)• Diffraction-limited optics• Emission laser with good phase
coherence– Longitudinal-mode operation– Long pulses (large coherence
length)• Return signal spot must be
coherent across most of itstransversal section– Van Cittert-Zernicke theorem
2. Refractive turbulence effects• Phase and amplitude distortion• Degrades signal coherence
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Conical scanning [θ,φ(t)], with zenith angle, θ, constant.Radial wind speed component along thelidar LOS at any time t is given by
( )[ ] ( )( )[ ] θ+φ−φθ=
=⋅=φcoscossin 0 wtv
strtv
H
rrr
VAD representation:Plot vs. the azimuth angle, φ,
⎪⎩
⎪⎨
⎧
θ=θφ=θφ=
seccscsincsccos
0
0
OSAwAvAu
( ) OSAAVAD +φ−φ= 0cos
VAD (VERTICAL AZIMUTH DISPLAY)VAD (VERTICAL AZIMUTH DISPLAY)
Clifford, S. T.; Kaimal, J. C.; Lataitis, R. J.; Strauch, R. G. Ground-Based Remote Profiling in Atmospheric Studies: An Overview. Proc. IEEE 1994, 82 (3), 313-355.
( )[ ]tvr φ
Wind components derived from amplitude, A, and offset, Aos
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GSIGNAL PROCESSING TECHNIQUESSIGNAL PROCESSING TECHNIQUES
MAIN LIMITATION• Temporal coherence (i.e., the time
that the atmospheric scatterers take touncorrelate themselves from and initialstate of “known” phase)
Doviak and Zrnic’s estimation
where σv is the velocity std (1 m/s).CONSEQUENCE
• Uncorrelated returns (τc << PRT)• fd canNOT be estimated as the rate
of change of the phase betweensuccessive return pulses,
vc σ
λ≈τ 1.0
( )dt
tdfdφ
π=
21
SIGPRO GOAL– Range-resolved vr estimate
METHODSSpatial windowing
• Estimate the Doppler shift withineach range “gate” (τwin).
Digital spectral-peak estimators• Basics:
Periodogram/autocorrelation• Periodogram, AR time series,
Capon estimator, Poly-pulse pairErrorbars: Cramer-Rao bound for
covariance estimatorsKey trade-off:
2;
4maxτ
=Δλ
<ΔΔcRcvR r
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Wind measurement example using a Doppler lidar at Eldorado Canyon during a mesofront invasion.
SOURCE: Courtesy of NOAA (National Oceanics and Atmospherics Administration).
COHERENT DOPPLER LIDARCOHERENT DOPPLER LIDAR
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GINCOHERENT DOPPLER LIDARINCOHERENT DOPPLER LIDAR
(or DIRECT DETECTION DOPPLER LIDAR)
EDGE TECHNIQUE (ET)• A Fabry-Perot or etalon used as frequency-to-amplitude transducer• fd is estimated by measuring the transmission change• Velocity accuracy → sprectrumsharpness → Mie’s peak is used
DOUBLE-EDGE (DET)• Two etalons symmetrically located around the REF laser line• Separation of aerosol/molecular Doppler returns
TECHNIQUESEdge-Technique (ET), Double-Edge Technique (DET), Fringe Technnique
SOURCE: C. Muñoz et al., “Speedmeasurementswith a continuouswave Lidarprototype,” Proc. IEEE IGARSS 2007, in press.
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FIG SOURCE:Sroga et al, “Lidar Measurement ofWind velocityprofiles in theboundary layer,”J. Appl. Meteor., 19, 598-607 (1980).
ELASTIC WIND LIDARELASTIC WIND LIDAR
KEYS• Airborne particles → moving
targets/inhomogeneities• Spatial correlation assumes
1)Shape-invariant pattern with time2)Uniform speed
METHOD 1: αº-width scanningAt sweep times t1, t2, we measure
( ) ( )2211 , tvrSStvrSS rrrr −=−=
Pattern-matching method:
( ) ( )∫ Δ+=ΔASS dArrSrSrR rrrr
21)(21
is maximum for ( )12 ttvropt −=Δ rr
Limitations: Decorr./ Low-scan speedsE.g. Aerosol patterns (mean ∅= 50m) advected at v=10 m/s would exist forapprox. D/v = 5 sScan (90º at 1º/step, 1s/step) = 90s!
METHOD 2: 3-azimuth scanTime-space lagging of
LOS range, Ri
φ1 φ2
( )nm tRSi
,φ
FIG. SOURCE: S. Tomás et al., “A wind speedand fluctuationsimulator forcharacterizingthe wind lidarcorrelationmethod,” Proc. IEEE IGARSS 2007, in press.
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Chap.5. Other Laser Radar Chap.5. Other Laser Radar SystemsSystems
Francesc Rocadenbosch
Remote Sensing Lab. (RSLAB)Universitat Politècnica de Catalunya
Campus Nord, D4-016roca@tsc.upc.edu
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DIAL SUMMARYDIAL SUMMARY
OPERACIONAL PRINCIPLE• DIAL (Differential Absorption Lidar)• Uses two (or more) tuning wavelengths, one of which is absorbed by the
atmospheric species of interest, and another one that is not.
( )( )( )RPRP
RN
aaa
λ′
λ
σ−σ′≈ ln
21
where:Na is the molecule concentration, are the molecule absorption cross-sections at and, are the backscattered return powers at , normalised to the transmitted ones.
aa σ ′σ ,λ ′λ ,
λ ′λ PP ,λ ′λ ,
Fig. Contours of NO2 concentration (ppm) in the vicinity of a chemical plant, as measured by differential absorption lidar. (SOURCE: K. W. ROTHE et al. 1974. Appl. Phys. 4, 181 (1974)).
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GDIAL SUMMARYDIAL SUMMARY
APLICATIONS1) Concentration of chemical species in the atmosphere, car exhausts, refineries,...Measurement types:
• range-resolved (RR), and• column-content (CC)• e.g., SO2, NH3, O3, CO, CO2,
HCl, vapor H2O, NO, N2O, SF6Typ. Resolutions: ppb to ppm. Typ. Ranges: a few kms.
2) Temperature and humidity
Fig. SOURCE: Whiteman, D. N.; Melfi, S. H. Cloud liquid water, mean droplet radius and number density measurements using a Raman lidar. J. Geophys. Res. 1999, 104 (D24), 31411-31419
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DIALDIAL
MEASUREMENTS:• Direct: Concentration of chemical
species in the atmosphere suchas
SO2, O3, C2H4, NH3, CO, CO2, HCl, H2O, NO, N2H4, N2O, SF6
• Indirect: Temperature andPressure
LASER TYPES:• Dye• CO2• Excimer• Ti:Sappire• Optical Parametric Oscillator (OPO)
INTERACTION
1νh1νh
GROUND LEVEL
VIRTUAL LEVEL
EXCITED LEVEL
0νh
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GDIALDIAL
MEASUREMENT PRINCIPLE1) Assume testing wavelengths, λ0 (center absorption line) and λW (wing)2) Consider
where
( ) ( ) ( )λα+λα=λα GA
• αG is the extinction coef. due to absorption by the gas of interest,
– where N is the gas concentration and σ its absorption cross section– within the range cell ΔR.
• αA is (...) due to scattering+absorption by all other constituents
( ) ( )λσ=λα NG
3) Measurement equation
( ) ( ) ( ) ( )[ ]( ) ( )[ ]⎩
⎨⎧
Δ+≤<Δα+α−λα−≤λα−
λβλ
=λRRRRRR
RRRR
RKRP
GAiA
iAi
ii
000
02 ,22exp
,2exp,,
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DIALDIAL
Computing the ratios,( )
( ) wii
i
RRPRP
λλ=λΔ+λ
λ ,,,
,ln 00
0
and solving for the gas concentration, N,
( )( )
( )( ) ( ) ( )w
w
w
RRPRP
RRPRP
RN λσ−λσ=σΔ⎥
⎦
⎤⎢⎣
⎡Δ+λ
λ−
Δ+λλ
ΔσΔ≈ 0
0
0
00
00 ,,
,ln,
,ln2
1
where we have assumed , i.e.,1) weak spectral dependence of αA and β in the region (λ0, λw)2) nearly simultaneous measurements
( ) ( ) ( ) ( )RRRandwAA Δ+λβ≈λβλα≈λα ,,0
MEASUREMENT SENSITIVITYMinimum detectable concentration,
[ ] ( )[ ] [ ] 02.0ln,.ln105 2
33 ≈ΔΔσΔ
Δ×= −−
typmin mRcmcmN
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ELIGHT SYSTEM SPECS:•Laser
– Ti:Sapphire, 790 nm (750-890 nm), 200 mJ, 20 Hz
– SHG, THG → 250-400 nm (UV), 5-25 mJ
•Telescope – 40-cm ∅, beam (5 cm, 200 mrad)
ΔR = 7.5 mΔt < 30 min
http://www.elight.de
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DIALDIAL
OPTICAL CONFIGURATION:
Target gases: 1) O3, SO2 (4 ppb), 2) toluene, bencene (10 ppb), NO2 (20 ppb)
http://www.elight.de
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Fig. SOURCE: INERIS - DRC-AIRE-00-23443-n° 535 Annexes A-C in www.lcsqa.org/rapport/rap/prog2000/ ineris/annexec_lidar_evaluation.pdf(Accessed June 2004).
Fig.1 Selection of λon and λoffwavelengths for toluene measurement.
Fig.2 Pollutant gas measurement sensitivity
Fig. 1
Fig. 2
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DIALDIAL
Fig. SOURCE: Well Test Flare Plume Monitoring–Literature Review. Report CCT-P 016.01, Carbon and Energy Management. Alberta Research Council Inc., Alberta (Canada). Dec. 2001.
SOME MEASUREMENT EXAMPLES
Fig. 1. NO2 horizontal emission in Geneva (Ref. Elight, GmbH)
Fig. 2-3. Methane Plume 130 m Downwind of Ship Loading Vent (CH4 concentration from 0 to 17 ppmv, Ref. Spectrasyne Ltd.)
Fig. 1
Fig. 2
Fig. 3
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GLONGLONG--PATH ABSORPTION LIDARPATH ABSORPTION LIDAR
OPERATIONAL PRINC.: “Long-path absorption”. See also TDLAS.
APPLICATIONSColumn-content (CC) gas detection
• Sensitivity defined by [ppm·m]
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LONGLONG--PATH ABSORPTION LIDARPATH ABSORPTION LIDAR
TDLAS (Tunable-Diode Laser Absorption Spectroscopy)Typ. an InGaAsP diode electronically swept around 1.31 µm or 1.55 µm
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GFLUORESCENCE LIDARFLUORESCENCE LIDAR
MEASUREMENTS:• Concentration of chemical species
specially in the upper atmospheresuch as
OH-, Na, K, Li, Ca, Ca+
• (...) lower atmosphere such asSO2, NO2, I2, NO, OH
• Oil slicks on water• Agricultural (chlorophyll, algae) • Marine baseline survey• Water temperature/salinitiy
LASER TYPES:• Dye• N2(λ = 337 nm)• Ne
INTERACTION
GROUND LEVEL(a)
EXCITED LEVEL
νhνh
EXCITED LEVELBAND
νh*νh
GROUND LEVEL(b)
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FLUORESCENCE LIDARFLUORESCENCE LIDAR
OPERATIONAL PRINCIPLE• The laser source is tuned to a molecule absorption
band that reradiates a fluorescence (red-shifted, i.e. towards a λ↑, either resonant (Fig.d) or wide-band (Fig.e)).
APLICATIONSDetection limited to a few minor atmospheric molecular constituents
• Return intensities are a few orders of magnitude larger than ordinary Raman scattering
• Difficult to determine absolute concentrations because of the uneven absorption of transmitted beam (atmospheric quenching)
• Ej. Biophysical stress and vegetation maps– Chlorophyll fluorescence F690/F735 nm
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GFLUORESCENCE LIDARFLUORESCENCE LIDAR
Fig. SOURCE: Measures (1992); R.M. Measures, "Laser Remote Sensing. Fundamentals and Applications". John Wiley & Sons, 1984. (Reprint de 1992, Krieger Publishing Company).
OIL-SPILL DETECTION AND IDENTIFICATION
Traditional sensors• e.g. multiband cameras, radar
mappers, IR scanners, microwave radiometers
• fail in classifying the oil type
Non-traditional: Laser flourosensor• Samples can be uniquely
characterized by measuring:– peak emission wavelength– lifetime– fluorescence efficiency Sufficient to make airborne
measurements
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FLUORESCENCE LIDARFLUORESCENCE LIDAR
EXAMPLE: THE US DOT (Coast Guard oil-sensing lidar)• Main specs:
– Mounted inside a marine helicopter (meas. altitude ≈ 40 m, 70 km/h)
– 100 kW, 10-ns N2 laser operating at 337 nm, 500 Hz
– 30-cm diameter, f/3.5 Newtonian telescope
– 35-channel Optical MultichannelAnalyzer (OMA)
• Two operation modes– (Mode 1) 2 of the 35 channels are calibrated for ambient sea-water fluorescence– (Mode 2) System is switched to the classification mode (full OMA activated)
• Classification method (3 main groups)– (Mode 1) Peak + fluorescence conversion efficiency at λcal1,2
– (Mode 2) Spectrum shape identification (e.g. Pearson’s correlation coefficient).
Fig. SOURCE: Measures (1992); R.M. Measures, "Laser Remote Sensing. Fundamentals and Applications". John Wiley & Sons, 1984. (Reprint de 1992, Krieger Publishing Company).
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GFLUORESCENCE LIDARFLUORESCENCE LIDAR
Fig. SOURCE: Canada Center for Remote Sensing (CCRS) & Measures (1992).
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FLUORESCENCE LIDARFLUORESCENCE LIDAR
Fig. SOURCE: Measures (1992); R.M. Measures, "Laser RemoteSensing. Fundamentals and Applications". John Wiley & Sons, 1984. (Reprint de 1992, Krieger Publishing Company).
BETTER CLASSIFICATION APPROACH:
Fluoresc. Decay Spectroscopy (FDS)MOTIVATION
• Modest classification: 3 types• More channels: Cost↑ and
SNR↓MEASUREMENT KEY
• Fluoresc. decay time as a function of λ
• is a spectral fingerprint of materials that allows fine discrimination.
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GOTHER LASER RADAR SYSTEMS: PART 1OTHER LASER RADAR SYSTEMS: PART 1
Fig. SOURCE: Measures (1992); R.M. Measures, "Laser Remote Sensing. Fundamentals and Applications". John Wiley& Sons, 1984. (Reprint de 1992, Krieger Publishing Company).
BATHYMETRYIt’s hydrographic lidar.MOTIVATION
• IR and MW radiation have negligible penetration in water
• Uses the blue-green “window on sea”
KEYS• Sounding Depth and bathym.
lidar equation depends on– αabs/αsca
– two-way (i.e., air-water and water- air) transmission factor
– beam spreading and diffusion on water medium → multipathattenuation (αmp)
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OTHER LASER RADAR SYSTEMS: PART 1OTHER LASER RADAR SYSTEMS: PART 1
THE SHOALS (Scanning Hydrographic Operational Airborne Lidar Survey) PROJ.
• Airborne– 400 Hz system– Collects 400 soundings/s and
every 4 m (variable spot)– Equals 16 km2/h
• Ground-based processing system
– depth-extraction algorithm (NOAA)
Sect. SOURCE: J.L. Irish, J.K. McClung, W.J. Lillycrop, “The SHOALS System”, Joint Airborne Lidar Bathymetry Technical Center of Expertise, US Army Engineers District in http://shoals.sam.usace.army.mil/pdfFig. SOURCE: Measures (1992).
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GOTHER LASER RADAR SYSTEMS: PART 1OTHER LASER RADAR SYSTEMS: PART 1
SHOALS APPLICATIONS(Fig. 1) Tidal inlet in Lake Worth (Flda).
• Quantify channel dredgingrequirements and nearshoreconditions
• Volumetry– Calculate sediment volumes for
navigation and nourishment projects
(Fig. 2) Tidal inlet in Long Island (NY).• Reveal the depth and extent of the
scour hole• Comparison with historical data
3-h SHOALS survey = Sveral days with a single-beam acoustic system!
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OTHER LASER RADAR SYSTEMS: PART 1OTHER LASER RADAR SYSTEMS: PART 1
SHOALS - Coastal Mapping - Port Huron (Lake Huron, Michigan)
• Navigation charts
MORE APPLICATIONS...• Sediment processes• Shoaling and dredging at
the port• Flux modelling
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GOTHER LASER RADAR SYSTEMS: PART 1OTHER LASER RADAR SYSTEMS: PART 1
SHOALS - Coastal Mapping - Solander Island, New Zealand• Very fine resolution as compared to acoustic survey vessels
• Need to update outdated navigation charts
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OTHER LASER RADAR SYSTEMS: PART 2OTHER LASER RADAR SYSTEMS: PART 2
PROFILOMETRY (I): TOF (Time of flight) principle
TOF Laser Ranging vs.
MechanicalE.G.http://www.simcotech.com/sensors/bannerlt3.htm
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GOTHER LASER RADAR SYSTEMS: PART 2OTHER LASER RADAR SYSTEMS: PART 2
PROFILOMETRY (II):AUTOFOCUS or INTERFEROMETRIC
• http://www.solarius-inc.com/html/autofocus.html
PHASE MODULATED• http://www.phaselaser
.com/sensors93.htm
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OTHER LASER RADAR SYSTEMS: PART 3OTHER LASER RADAR SYSTEMS: PART 3
ACTIVE IMAGING (I): Spectrally selective vision
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3D ACTIVE IMAGING (II)• (OPTECH, ILRIS 2D)
http://www.optech.on.ca/
Downtown Florence, with Basilica at top left (Italy Area: 4 x 2 km)
SPECS:
PRF: 5 kHzDuration: 45 minScan Freq: 15 HzScan Angle: ±19°Alt.: 450m AGLPoints: 100,000
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OTHER LASER RADAR SYSTEMS: PART 3OTHER LASER RADAR SYSTEMS: PART 3
ACTIVE IMAGING (III):CMS (Cavity Monitoring System)
Volume computation (VCMS) and TOF imaging
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GFREEFREE--SPACE OPTICAL COMMUNICATION LINKSSPACE OPTICAL COMMUNICATION LINKS
ADVANTAGES:• Lower mass, weight and volume of TXT/RTX systems• Laser beams: narrower ⇒ higher power densities• No restrictions in the use of frequencies / bandwidths
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FUTURE TRENDS IN LASER RADARFUTURE TRENDS IN LASER RADAR
CONCERNING:LIDAR SYSTEMS ARCHITECTURE
• System simplification and reliability• Operation in autonomous automated routine regime
TECHNOLOGYCAL TRENDS• Semiconductor diode laser technology• If the application allows it, use of eyesafe lasers (λ > 1,5 µm) and/or
low enough power levels
OTHERS• Multisensor data fusion• Efforts in the methodology of data interpretation
Recommended