Transcript Document

The K-meter Survey System (KSS) Ksys:
A Synoptic Ocean Optical Measurement
David M. Allocca
Brian M. Concannon
V. Michael Contarino
Thomas P. Curran
Linda J. Mullen
Jennifer E. Prentice
Electro Optic and Special Mission Sensors Division
NAVAIR, Code 456, Building 2185 Suite 1100
22347 Cedar Point Road Unit 6
Patuxent River, MD 20670-1161
Experimental Data
 Office of Naval Research sponsored HyCODE 2001 test
 NAVAIR invited to take lidar data from R/V Endeavor
 Extensive in-situ measurements (SLOWDROP, Pegau)
Synoptic Measurements = Snapshots
Data collected over an area as rapidly as possible to
eliminate time related variations
-Pickard& Emory
Approach
Observations made of specific features reduced to as simple
a statement as possible of the character of the features
themselves and their relationship to other features
-Pickard& Emory
Ocean LiDAR
A perfect example of a Synoptic Measurement
Rapidly and Accurately survey an area at high speed if the
optical characteristics of the area are suitable
What is Ksys?
Po, FOV, Div
h
d
a, b, c, b, n
Returned Optical Signal
 System Attenuation Coefficient
 An Apparent Optical Property
 Water Clarity
Air
H 2O
P(d) =
AP0 e
-2Ksys d
2
(n h + d)
Where :
Time = Depth
Returned Optical Power vs. Depth
is a function of :
- system parameters
- water IOP’s
A includes system parameter effects,
air-water transmission and b(p)
Po = transmitted power
h = height above surface
n = water index of refraction
d = water depth
Shipboard K-Meter Survey System (KSS)
1nm Interference Filter
Receiver Lens
Adjustable Iris
PMT
LASER
CH 2
Divergence Lens
Attenuator
Window
.25” Aperture
Steering Mirrors
CH 1
Receiver Lens
PMT
Adjustable Iris
Pentium IV
Computer
with:
GPS
Digitizers
Pitch & Roll
1nm Interference Filter
KSS Shipboard Optical Layout
Shipboard System Design Specs
o
o
Div = 4.3 , CH 1 FOV = 10 , CH 2 FOV = 4
Dual Independent 4” x 4”, ND of 2.6 to 4
Output Power: 100mJ @ 532 nm
7 nS Pulse Width
100Mhz Analog Bandwidth
8 bit, 1 GSPS Dual Digitizers
PMT Photo Detectors with 10% QE
Interference Filters with 4 nm Bandwidth
o
Airborne K-Meter Survey System (KSS)
Aircraft Altitude: 500fT
Laser Spot Size @ 500fT: 50fT
Div = 3o, FOV = 6o
Dual Channel Receiver Aperture 5” diam.
Output Power: 2.5mJ/Pulse @ 532 nm
4nS Pulse Width
Repetition Rate: 0.5 hertz
8 bit, 1 GSPS Dual Digitizers
Log Amps: 4 decades of compression
PMT Photo Detectors with 10% QE
GPS: Trimble GPS unit
Pitch and Roll: Self contained IMU; 1o accuracy
Beam Steering
Wedge
Filter
Beam-splitter
Log Amps
Power Supplies
Lens
Turning
Mirror
Field
Lens
PMT’s
532nM Laser
Inertial Unit
System is “Eyesafe” for 12cm Optics at 500 Ft.
HyCODE 2001 – NAVAIR Station Locations
25,000 Ksys Waveforms Collected On Station and In Transit July 22-25
Typical Sample
=
40 waveforms
Waveforms processed to
yield an average Ksys
point measurement for a
given depth range
e.g. (1-15 m)
Lidar Signals for Different Water Types
0.8
Clean Return
Dirty Return
Clean Ksys
Dirty Ksys
0.7
0.6
0.4
Clean
Enroute Sta 2 - 3
Dirty
0.3
Sta 13
0.2
0.1
0
0
5
10
15
Depth (m)
20
25
30
ksys (/m)
LOG(volts)
0.5
Comparison of Lidar and In-situ Profile Data
Shallow Mixed Layer at Station 10
KSS Transect Data, Stations 2 to 10
>500 Ksys Samples
0.300
Ave. Ksys CH1
Ave Ksys Ch2
Sta Num
Ksys (/m)
0.250
0.200
CH 2
Narrow FOV
0.150
CH 1
Wide FOV
0.100
9
7
8
5
6
4
2
3
0.050
0.320
0.071
0.270
0.064
c(532) [Pegau slowdrop]
a(532) [Pegau slowdrop]
0.220
0.170
-73.4
-73.2
-73
-72.8
-72.6
0.057
-72.4
-72.2
Longitude (deg)
-72
-71.8
-71.6
-71.4
0.050
-71.2
a (/m)
c (/m)
10
ONR HyCODE KSS Data
Stations 8 to 7
Log (Return Signal)
0
0.4
-5
0
Depth (m)
New Jersey Coast, Mid-Atlantic Bight
0.2
-10
5
10
15
20
Inshore to Off-Shelf, West to East Transect
25
30
2
Depth (m)
4
6
8
10
12
14
-72.81
Ave. Ksys
(/m)
39.51
0.25
0.20
0.15
0.10
-72.78
-72.75
-72.72
-72.69
Longitude (deg)
-72.66
-72.63
39.52
0.6
Key West KSS Data
Log (Return Signal)
0.2
0.4
0.6
Near surface material
(Sargassum Weed)
distorts waveform (close
to x10 near surface
return) and therefore
changes Ksys
-10
-5
0
5
10
15
20
0.2
0.4
-5
5
10
15
20
25
30
North to South Transect
30
2
Depth (m)
0.6
Ksys is fairly
homogonous
through 15 m
(ksys ~ 0.08)
0
25
5
8
11
14
Avg. Ksys
(/m)
Depth (m)
0
-10
Depth (m)
0
Log (Return Signal)
0-81.7981
24.23082
0.12
0.10
0.08
0.06
2
4
6
8
Distance Along Track (km)
-81.8049
24.31415
10
Future Work
January 2002
Science Missions :
Validate lidar waveform model using in-situ data
Solving the forward problem (IOP inputs gives lidar waveform)
Reverse problem
Can a unique set of IOP’s be derived from a single lidar measurement ?
Detect, identify and monitor shallow water column structures
For example: plankton and particle scattering layers
Navy Mission :
Sensor performance predictions - TDA
Generate global maps of water clarity versus season
Mixed layer detection and mapping
We Need A “Forward” Model
IOPs
(a, c, b…)
Environment
(sea state, …)
Lidar
Model
Lidar Response
Ksys
System
(FOV, div, …)
Dr. Eleonora Zege of Belarus has developed a complete LiDAR
model for NAVAIR called KSS-2
HyCODE has provided a unique opportunity to compare
experimental measurements with lidar model results.
Our Model KSS2 – Inputs
Inputs
 System Configuration (FOV, Div.)
 System Geometry (Altitude, etc.)
 Transmit/Receive Characteristics
 Atmospheric Visibility
 Sea Surface Condition
 Water Optical Properties (stratification)
 Phase Function
System and Model Parameters
4” aperture & filter
8m
CH2 4.3
CH1 10.7
20
T x 3.3
20 km Vis.
Winds 5 to 12 knots
1.9
0.17
1.7
0.16
1.5
0.15
1.3
0.14
1.1
0.13
0.9
0.12
0.7
0.11
c (532) (/m)
a, c profiles
a (532) (/m)
Station 17
0.18
Lidar
Model
0.5
0.1
0.3
0.09
0.1
0
5
10
15
20
Depth (m)
OCEAN Phase Function (Petzold)
Our Model KSS2 – Outputs
Outputs
 LIDAR return profiles
 Components of the return profile
(Atmosphere, surface, water)
 Lidar decay rate (Ksys[depth])
 Shot noise and surface noise
Station Locations of Simultaneous Data
HyCODE 2001 Stations with Simultaneous Data
41.5
41
40.5
1
Latitude
40
39.5
7 6 5 4
17
39
LEO-15
38.5
July 22 to July 25, 2001
38
37.5
-76
-75
-74
-73
Longitude
-72
-71
0.45
0.1
0.4
0.09
0.35
0.08
0.3
0.07
0.25
0.06
0.2
0.05
0.15
0.04
Station 5
Homogeneous to 15 m
w = 0.78, a = 0.05, c = 0.18
c (532) (/m)
a (532) (/m)
Station 5
0.11
Excellent slope agreement
from surface to system noise
0.1
0
5
10
15
20
Depth (m)
Station 5
All lidar samples are an
average of 40 surface-aligned
waveforms
&
normalized to the peak of the
CH 1 experimental waveform
Normalized Signal
1
CH1 KSS
CH2 KSS
CH1 Model
CH 2 Model
0.1
0.01
0.001
0.0001
0
5
10
Depth (m)
15
20
0.45
0.1
0.4
0.09
0.35
0.08
0.3
0.07
0.25
0.06
0.2
0.05
0.15
0.04
Station 6
a flat with some variability in c
w = 0.82, a = 0.06, c = 0.27
c (532) (/m)
0.11
Excellent agreement 5m to
system noise
0.1
0
5
10
15
20
Depth (m)
Station 6
1
Station 6 surface peak
predicted by the model
not evident in
experimental data
Details, details…
Normalized Signal
a (532) (/m)
Station 6
CH1 KSS
CH2 KSS
CH1 Model
CH 2 Model
0.1
0.01
0.001
0.0001
0
5
10
Depth (m)
15
20
1.9
0.17
1.7
0.16
1.5
0.15
1.3
0.14
1.1
0.13
0.9
0.12
0.7
0.11
0.5
0.1
0.3
0.09
Station 17
Shallow turbid layer to 15m
w = 0.91, a = 0.16, c = 1.6
c (532) (/m)
0.18
Excellent agreement from near
surface to system noise
0.1
0
5
10
15
20
Station 17
Depth (m)
1
Analog BeamWidth in
the model is 2X > the
KSS
Is this fair?
Yes.
Correct system BW and
pulse shape needed for
KSS2 inputs
Normalized Signal
a (532) (/m)
Station 17
CH1 KSS
CH2 KSS
CH1 Model
CH2 Model
0.1
0.01
0.001
0.0001
0
5
10
Depth (m)
15
20
0.1
0.4
0.09
0.35
0.08
0.3
0.07
0.25
0.06
0.2
0.05
0.15
0.04
Station 7
c (532) (/m)
0.45
Strong, thin scattering layer > 10 m
w = 0.81, a = 0.06, c = 0.26 (0.4)
Lidar and model track, including
layer, to limits of system noise
0.1
0
5
10
15
20
Station 7
Depth (m)
1
This is great.
Normalized Signal
a (532) (/m)
Station 7
0.11
CH1 KSS
CH2 KSS
CH1 Model
CH 2 Model
0.1
0.01
0.001
0.0001
0
5
10
Depth (m)
15
20
What Parameters have the greatest impact on Ksys?
Is there a unique set inputs for each Ksys?
Inverting the Model : New Scenario
KSS Ksys
Inverted
Model
Unique Set
of IOPs?
Conclusions
 Excellent agreement between experimental and
modeled data in upper two decades
 Model agrees within input errors
 Must pay attention to details
Future Work
 Apply measured phase functions
 Apply actual system bandwidth and pulse width
 Reduce system noise
 Think about inversion problem
 Be ready for next opportunity
NAVAIR Research Interests Related to HyCODE
Lidar sensitivity to total Backscatter (bb) and VSF vs. Absorption (a)
Sensitivity to Estimated vs. Direct, in situ measured VSF
Value of using polarization changes to differentiate water column
constituents
Increase KSS Depth Resolution - Present System, 0.3-1 m
Higher Res. System Modifications for Sub-meter scale Observations
?Required vs. Desired?
1) Precisely defined pulse shape
2) Shorter pulse (1-3 ns) more power laser, Greater PMT Detector
Bandwidth (500 MHz) or IPD with 1 GHz bandwidth, Narrow
FOV and DIV… we have most of this but they are system changes
25, 000 Waveforms
reduced to 40 Shot
Samples, Corrected for
the Log Amp, PMT nonlinearity, R2 Loss
Designation by:
LEO
2001 Sample Date
Sample Time
LPR2.txt
What to do with data
document.