introduction to lidar (laser radar) remote sensing · pdf fileintroduction to lidar (laser...

(C) 2007

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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)

[email protected]

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NS Introduction to LIDAR Remote Introduction to LIDAR Remote

Sensing SystemsSensing SystemsChap.1 Optical and Technological

Considerations



Campus Nord, [email protected]

IGARSS 07, (C) F. Rocadenbosch (RSLAB)

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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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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:


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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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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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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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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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


SOURCE: J. Hecht,Understanding Lasers,IEEE Press.


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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





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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

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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

∞

11


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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

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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

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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





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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)

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GTEMPERATURE MEASUREMENT (IITEMPERATURE MEASUREMENT (II))


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)


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)

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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).

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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

= ,,,,*

10


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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:

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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

1

(C) 2007

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Chap.4. Wind Chap.4. Wind LidarLidar SystemsSystems





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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.

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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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ad

sc

λ≈

θλ

=ρ 61.022.1

1.22 0.61cs

da

λ λρθ

≈ =









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










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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).


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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





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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

3


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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

4


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GDIALDIAL

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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GDIALDIAL

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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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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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).


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Fig. SOURCE: Canada Center for Remote Sensing (CCRS) & Measures (1992).


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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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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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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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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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PROFILOMETRY (I): TOF (Time of flight) principle

TOF Laser Ranging vs.

MechanicalE.G.http://www.simcotech.com/sensors/bannerlt3.htm

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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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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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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

introduction to lidar (laser radar) remote sensing · pdf fileintroduction to lidar (laser...

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