DEP. OF SIGNAL THEORY AND COMMUNICATIONS
Chap.4. Elastic Lidar Systems
Francesc Rocadenbosch
ETSETB, Dep. TSC, EEF Group
Campus Nord, D4-016
roca@tsc.upc.edu
(C) 2005
SUMMARY
ELASTIC INTERACTION
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
MEASUREMENTS:
• Direct:
Aerosol/molecular composed
intensity returns
• Indirect:
(Usually requires calibrating
conditions/hypotheses)
Optical parameters, pollution
concentration and flux rate, wind
LASER TYPES:
• Ruby ( = 694.3 nm, 347.2 nm)
• Nd:YAG ( = 1064, 532 nm, 355 nm)
• Excimer ( ~ 350 nm)
F. Rocadenbosch, 2005
VIRTUAL LEVEL
h
h
GROUND LEVEL
(b)
Types of interaction:
1) Rayleigh scattering
(molecules, r << )
2) Mie scattering
(aerosols, r  )
Types of elastic lidar:
1) Backscatter lidar
2) Doppler lidar
2
APPLICATIONS
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
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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3
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
ARCHITECTURE (I)
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4
ARCHITECTURE (II)
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
RECEIVING OPTICAL
SYSTEM
• Telescope
– “optical antenna”
– effective area, Ar
rd
FOV 
[rad ]
f
• Inteference filter
– limits background
power
Pback  Lb  Ar dd
• O/E converter
– Photodiode, PMT
– Conditioning chain
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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5
SPATIAL RESOLUTION (I)
INTERACION OF A LIGHT PULSE WITH THE ATMOSPHERE
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
t 
c
R
LIDAR
R1  c ( to   ) 2
R0  c t 0 2
c (t o   )
c to
Location of light
pulse at t  t
o
Cell producing the
backscattered radiation
arriving to the lidar at
t  t0
• 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.
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6
SPATIAL RESOLUTION (II)
SPACE-TIME DIAGRAM
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
(rectangular-shaped laser pulse, L)
Using analog recording
(d=0),
c L
Ra 
2
Using a time detection
window of length d=1/fs
(e.g., A/D sampling, photon
counting),
c  L   d  c d

R 
2
2
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7
THE (ELASTIC) LIDAR EQUATION (I)
N  Particle concentration [part/m3]
WITHIN THE SCATTERING
VOLUME:
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
d()/d  Backscatter crosssection per solid-angle unit [m2/sr ]
  Backscattering coef [m2/m3sr]
r=R
 = N d()/d [m-1sr-1]
R
2
=Ar/R2
R
Ar
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THE (ELASTIC) LIDAR EQUATION (II)
BASIC INTERVENING MAGNITUDES
E
L
2) Incident power density on the atmospheric resolution cell, Ein [W/m2]
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
1) Laser emitted power per pulse (L), P0 [W ]
E in R  


P0
R
exp

0  ( u ) du ,
2
r
P0 
r  R
3) Cell-backscattered power per solid-angle unit, Ksca [W/sr]
K sca R    R E in R V
with
 V  r 2 R

 R  c L 2
4) Backscattered power collected by the telescope, P(R) [W]
A
P R   K sca R  exp  0R  ( x ) dx ,   r2
R
5) Finally,
E 2c Ar
R


P R  

R
exp

2
0  u du
2
R



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
9
THE (ELASTIC) LIDAR EQUATION (III)
Elastic LIDAR Equation (simple scattering)
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)

where:

R
K
P , R   2 , R  exp  2 0 , r dr R 
R
, R  atmospheric optical extinction coef. [m-1]
, R  atmospheric optical backscatter coef. [m-1sr-1]
d   
– where
,
  , R   N R 
d
– N is the average density of aerosols + molecules [m2/m3sr]
 R 
overlap factor [ ],
P R 
optical return power [W]
K
where:
0  R   1
system constant [W
m3 ],
K
Ec
Ar
2
E
(peak) energy [J]
Ar
effective telescope area [m2]
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THE LIDAR EQUATION (IV)
ATMOSPHERIC OPTICAL
COEFFICIENTS
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
SOURCE: Measures (1992).
Concerning the lidar Eq., note
that:
 R   aer R   mol R   abs R 
0
  R    aer R    mol R 
Fig. SOURCE: R.T.H. Collis and P.B. Russell,
“Lidar Measurement 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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11
THE LIDAR EQUATION (V)
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
FURTHER COMMENTS:
1) Assuming a homogeneous atmosphere and ideality system conditions,
the lidar equation takes its simplest form:
K
P(R) = 2  exp 2R 
R
backscatter
transmittance
2) Note the LIDAR optical thickness (COT) and related transmissivity!
R
T( , R)  exp 2COT R  ; COT R    ( , r)dr
0
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THE LIDAR EQUATION (VI)
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
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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13
THE LIDAR EQUATION (VII)
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
OVF OPTICAL ALIGNMENT
azimuth adj.
elevation adj.
Atmospheric laser foot-print
imaged is (telesc. far-field):
f
y i =   W o2 +  2 R 2  d o  R
R
f     f R    
yi = 


 



A)

size
y  position
f
 W 0  
=

f R    
y
B) i

 

R

y  position
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size
14
THE LIDAR EQUATION (VIII)
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
1
4 OK
2
brightest
area
REF
3
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THE LIDAR EQ. (IX): BASIC INVERSIONS
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
RANGE CORRECTION (R2P):
Backscatter-transmittance plot
Reveals atmospheric structure
• Mixing aerosol layer
• Cloud structure
CEILOMETRY:
Cloud-height extent monitoring
• Cloud base, peak, top
• No. of layers
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THE LIDAR EQ. (X): BASIC INVERSIONS
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
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. CHAIN
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
P(R)
R’V
V(R)
Ideal ADC
ntot
q
Vos
xa+xs
V(R)  R VLP(R) VOS  ntot (R)  q  x a (R)  x s (R)
R’V: Net Voltage Responsivity (V/W)
Vos: Total system offset (user+drift+background)
ntot: Total noise (photodetection + electronic)
q: Quantization noise
xa,s: A/Synchronous interferences
VOS
 R v PBack  Vdrift  Vuser  
dVdrift
Δt
dt
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unwanted terms
Sampling at fs, detection
time d=1/fs, so that
c d
c
R 

2
2 fs
18
SIGNAL CONDITIONING (II): KEYS
RECEIVER CHAIN
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
1) Mapping function
V ( R )  RiG P ( R )  VOS
2) Operational settings
a) Map B to -Vmax
P ( R  )  Pback
VOS  Vmax  RiGPback
b) No ADC saturation
G
Vmax  VOS
Ri Pmax
3) Intensity Display
V R   V ( R )  V  
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EXAMPLES OF REAL SYSTEMS: RSCH. AGENCIES
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
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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BACKSCATTER LIDAR & RESEARCH AGENCIES
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
LITE (Lidar In-space Technology Experiment)
SOURCE:
http://www-lite.larc.nasa.gov/
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DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
BACKSCATTER LIDAR & RSCH AGENCIES
OTHER PROJECTS (ESA)
• ATLID: similar to LITE (NASA)
• ALADIN: wind lidar space-borne sensor
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EXAMPLES: MICRO-LIDAR
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
CLOUD AND AEROSOL M-LIDAR
MAIN FEATURES:
• Self-alignment of emission and
reception axes
• Eye-safe
• Compact and portable
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SOURCE:
CIMEL
Electronique,
http://www.cimel.fr (Mod. CE370-2)
23
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
EXAMPLES: BACKSCATTER LIDAR - UPC 1996
LASER
Nd:YAG
Gain medium
0.5 J/532 nm
Energy
0.1mrad
Divergence
10 ns
Pulse length
10 Hz
PRF
RECEIVER
2m
Focal length
20 cm
Aperture 
APD (EGG C30954)
Detector
Net Responsivity 6101-3106 V/W
10 MHz
Bandwidth
SYSTEM SPECS
Vertical biaxial
Configuration
70 fW·Hz-1/2
System NEP
Min. Det. Power < 5 nW
20 Msps/12bit
Acquisition
Spatial resolution 7.5 m
DISTINCTIVE
SPECS:
(as compared to
W RADARS)
R = 7.5 m!
t = 1 min
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DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
BACKSCATTER LIDAR - UPC 1996
LASER
Nd:YAG
Gain medium
0.5 J/532 nm
Energy
0.1mrad
Divergence
10 ns
Pulse length
10 Hz
PRF
RECEIVER
2m
Focal length
20 cm
Aperture 
APD (EGG C30954)
Detector
Net Responsivity 6101-3106 V/W
10 MHz
Bandwidth
F. Rocadenbosch, 2005
SYSTEM SPECS
Vertical biaxial
Configuration
70 fW·Hz-1/2
System NEP
Min. Det. Power < 5 nW
20 Msps/12bit
Acquisition
Spatial resolution 7.5 m
25
ADVANCED CONFIGURATIONS: SRL - UPC 2004
Fig. 2
Polarim. Subs. (T)
Alignment
Fig. 3
Polarim. Subs. (R)
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
Fig. 1
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DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
SRL (UPC 2004)
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27
EXAMPLE
OF
BAD #Packets:
SIGNAL
CONDITIONING
Vout. File:
d7091951.
1. #IP/shot:
500. Rmin: 0
-5
x 10
2
(g)
(e)
6
V(R) [V]
inset (c)
0
0
2
4
6
R [km]
8

-2
10
(f)
8
2
0.08
0.06
0.04
8.5
9
R [km]
9.5
5 0 0
q
inset (d)
0.02
0
10
-3
(h)
5
2
R ·P(R) [W·km ]
2
2
x 10
0.1
-0.02
4
0
R ·P(R) [W·km ]
V(R) [V]
1
0.5
2
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
1.5
4
3
wrong V()
correction
2
1
0
0
2
4
6
R [km]
8
10
-1
F. Rocadenbosch, 2005
8.5
9
R [km]
9.5
28
Vout. File:OF
o4100110.
#Packets:
1. #IP/shot:
1000. Rmin: 0
EXAMPLE
GOOD
SIGNAL
CONDITIONING
-3
x 10
1.4
(a)
1.2
7
V(R) [V]
V(R) [V]
0.8
inset (c)
0.6
0.4
5
4
3
0.2
2
0
1
-0.2
0
0
5
10
15
10
10.5
11
R [km]
R [km]
x 10
0.8
(b)
-4
(d)

0.6
1 0 0 0
q
4
0.5
0.4
inset (d)
0.3
0.2
3.5
3
0.1
0
11.5
4.5
V(R) [V]
R ·P(R) [W·km ]
2
0.7
2
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
1
LIDAR (LASER RADAR)
(c)
6

0
5
10
15
2.5
13
R [km]
F. Rocadenbosch, 2005
1 0 0 0
q
13.5
14
R [km]
14.5
15
29
WINDOWED EXPLORATION (I)
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
CONCEPT
–We
accommodate
range A-B into the ADC
at the odd pulses and
C-D at the even ones.
–Hence,
ADC
range doubles!
dyn.
REQUIREMENTS
1) Each window is
defined by a set
(G, VOS, Rmin)
2) Synchronous G
and Vos update
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DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
WINDOWED EXPLORATION (II)
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31
SRL SYSTEM CONFIGURATION
ATMOSPHERE
POWER
METER
bus
MASTER
CLOCK
bus
FREQ.
ROUTING
STEPPING RS-232
MOTORS
bus
DIGITAL APD
RECEIVER 2
DIVIDER
RS-232
SYNCHRO
bus
UNIT
Data in
PHOTON
COUNTER
RAMAN
RECEIVER 3
UNIT
MUX
DIGITAL APD
RECEIVER 1
TELESCOPE
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
LASER
optical
fiber
Data in
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PSEUDO-RANDOM SYSTEMS
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
PN SEQUENCES (I)
KEYS:
ak
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
N  2n  1
i.e., period = NTb
ak
3) Usually, the binary polar
NRZ sequence is used,
ak  2ak  1
Fig. SOURCE: Takeuchi et al, “Random modulation CW
lidar”, Appl. Opt., 22(9), 1382-6 (1983).
F. Rocadenbosch, 2005
 t  kTb 

a t    2ak  1 
k
 Tb 
33
PSEUDO-RANDOM SYSTEMS
PN SEQUENCES (II)
Raa    
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
4) Periodic Autocorrelation
N 1    1
    ,
N
 Tb  N

NTb
2
 1 j0
~
Raa  j    1
 N j  0
 N2 N1  Nl j  0
~
Raa n   
 0 j0
5) Reencounters the system
(atmospheric) impulse
response 
• System identification
• Demodulation is
substituted by correlation
g (t ) 
c
1
Ar 2 R T R 2  R 
2
R
x t   Ea t   P0Tb a t 
~
~
~


y
t

x t   g t 

~
gˆ t   ~
y t   a t   g t 
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34
PSEUDO-RANDOM SYSTEMS
THE ATMOSPHERIC ID. PROBLEM
• The impulse excitation is substituted by
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
~
Rss t   l Eb t 
SYSTEM LAYOUT
Fig. SOURCE: Bundschuh et al., “Feasibility study of a compact low cost correlation LIDAR using a pseudo-noise
modulated diode laser and an APD in the current mode”, IEEE (1996).
F. Rocadenbosch, 2005
35
PSEUDO-RANDOM SYSTEMS
DEP. OF SIGNAL THEORY AND COMMUNICATIONS
LIDAR (LASER RADAR)
PROTOTYPE EXAMPLE
Fig. SOURCE: Takeuchi et al, “Diode-laser random-modulation
CW lidar”, Appl. Opt., 25(1), 63-7 (1986).
F. Rocadenbosch, 2005
36