Scaling Surface and Aircraft Lidar Results for Space-Based Systems (and vice versa) Mike Hardesty,...

Scaling Surface and Aircraft Lidar Results for Space-Based Systems (and vice versa)

Mike Hardesty, Barry Rye, Sara TuckerNOAA/ETL and CIRESBoulder, CO 80305

Working Group on Space-based Lidar Winds

Why scale ground-based and airborne measurements?

• Current predictions of spacebased lidar performance are based on models

• Models must assume values for key parameters such as laser beam quality, laser pulse stability, receiver efficiency, detector noise characteristics, and backscatter

• Using data from current systems tells us how well we are doing now

• Scaling question: How would an existing system do if it were looking at the same backscatter from space, but with pulse energy, range, range gate length, receiver aperture, and pulses accumulated scaled to match a space-based system

• Or, vice versa: If the specifications for a proposed space-based system were scaled to measure from the ground, what performance should it see?

• Effectively, we are scaling everything but the system efficiency


Some other points….

• A key uncertainty (especially for coherent systems) is the backscatter. For selected cases, we don’t know if the backscatter is representative or anomalous, we only know what the space system would see looking at the same volume of atmosphere

• If ground-based system scaling to space shows that the current instrument does not perform consistent with the model, we can then peel the onion another layer and look at the assumed model efficiencies and compare with system values

• Scaling high prf, low energy instruments used on the ground to space (where higher energies and lower prfs are likely to be used) will ideally take into account issues such as transmitted pulse characteristics and background noise effects, which may differ

Parameter Coherent CNRWavelength (microns) 2.05

Energy/pulse (Joules) .250

PRF (design) (Hz) 10

Optical Eff (total) .7

Mixing Eff .4

Detector Eff .8

Collector Diam (meters) .2

Backscatter* 3e-8

Transmission* 0.958 (one way)

Cn2 0

Bandwidth 50

200 400 600 800

-20

-10

0

10

20

30

40

Range (km)

CNR (dB)

CNR vs Range, Constant β

CollimatedFocus at Range

Using the parameters in the above table, with a nadir view and constant backscatter, coherent models show that the CNR @ 830 km would be -26.6 dB.

At 30 deg, the 830 km orbit translates into a ~960 km maximum range and we find CNR @ 960 km is approximately -28 dB

If we had a “ground-based” system with the above listed parameters, but had only 1.1 μJ of pulse energy, and if we focus the beam at the 2km altitude, we should be able to get the same -28 dB return at a 2km altitude/range (zenith looking).

If we had a collimated beam, we would need 70 μJ to see –28 dB.

We would like to see -12 db (minimum). This would require 40X more energy or 2.8 mJ total.

Reducing the aperture diameter to 8 cm, would mean that the system only needs 0.7 mJ to see -12 dB at 2 km.

HRDL needs 1.5 mJ to see this type of signal under the model conditions. Let’s try inverting HRDL…

Coherent Detection: NPOESS Orbit

Note that these calculations were done with constant transmission, constant backscatter, and infinite coherence length.

0 0.5 1 1.5 2 2.5-20

-15

-10

-5

0

5

Range (km)

Wideband SNR Mean Wideband SNR - HRDL NEAQS 2004

beam #

Range gate

8/11/04,02:00 wideband SNR. El:2.1°

100 110 120 130 140 150

1

2

3

4

-20

-15

-10

-5

0

5

Coherent system Parameter

HRDLSpace system

Wavelength (microns) 2.012 2.05

Energy/pulse (mJ) 1.5 250

PRF (Hz) 200 10

Pulse Length (ns) 200 500

System Eff .14 .14

Collector Diam (cm) 8 20

Bandwidth 50 50

Focus (km) 2.5 Collimated

Range (km) 2 958

Range gate (m,samp) 30,10 500,166

Pulses averaged 100 120

Scaling factor 1 -22.2 dB

CNR -11 dB -33 dB

# photons/estimate ~80 ~19

Degeneracy 0.32 0.005

Coherent Detection

Parameter Value

Wavelength 2.05 microns

Energy/pulse 5 mJ

Receiver Aperture Diam. 9 cm

PRF 80 Hz

Sampling Rate 100 MHz

Search bandwidth 50 MHz

Points per gate 64

Gate Width 96 meters

# pts in FFT 256

# bins in signal BW 11 = 4.3 MHz

# bins in search BW 128 = 50 MHz

Regarding the processing of this data, the following should be noted• The mean was removed from the time-series data for each pulse, at each range gate, before the spectra were calculated and averaged. • CNR Calculations are based on averaged spectra (for each range gate) calculated using 100 pulses. This spectral averaging reduces the variance on the signals, but does not affect the CNR amplitude.• Gates are independent (i.e. not overlapping)• All spectra have been whitened by dividing them by the “noise spectrum”. This noise spectrum was calculated by averaging the spectra over range ( range gates 50 to 59 where there was no return signal) and over time (the 100 pulses)• No filtering or demodulation has been applied to the data. S. Tucker

NOAA ET2303.497.4684

Wideband CNR for system with parameters at left

Coherent Detection - TODWL

1 2 3 4 5 6 7 8-14

-12

-10

-8

-6

-4

-2

Range (km)

CNR (dB)


Focus = 3.16 kmCollimated

β = 3×10-8

0 10 20 30 40 500

5

10

15

20

Frequency (MHz)

Spectral Amplitude

Spectrum at Range Gate # 25 = 2.40 km

0 10 20 30 40 500

5

10

15

20

Frequency (MHz)

Spectral Amplitude


0 10 20 30 40 500

5

10

15

20

Frequency (MHz)

Spectral Amplitude


0 10 20 30 40 500

5

10

15

20

Frequency (MHz)

Spectral Amplitude


This range gate is after the hard target. For these ranges, the CNR estimate actually reflects a signal bandwidth worth of noise (around the peak noise frequency) ratio, rather than a carrier signal to noise ratio.


The total power in the signal bandwidth is given by summing those values in the frequency bins +/- 5 bins from the peak frequency

0 1 2 3 4 5 6-30

-20

-10

0

10

20

30

40

50

LOS Range (km)

Amplitude (dB)

Return Signal Figures of Merit

Power in signal BWWideband CNRNarrowband CNR(peak-P

ns)/P

ns

nsBW

nsBWf

nb PN

PNPCNR sig

−=

nswb

nswbf

wb PN

PNPCNR sig

−=

( )∑∈

=SignalBWi

sigf ifPsig

Wideband and Narrowband CNRs are then calculated as follows:

Where Pns is the average noise power (approximated by 1 after whitening) , NBW is the number of bins in the signal bandwidth (11) and Nwb is the number of bins in the spectrum (Nwb = NFFT/2 = 128). The 11/128 ratio is equivalent to the 4.3 MHz to 50 MHz (signal BW to total search BW).


Summary:

• According to CNR models, the space-based system (with parameters listed above) would see a CNRWB of -29.4 dB at the 2km altitude (or 960 km range, see plot at left).

• The TODWL system sees approximately -2 dB of signal at most ranges of interest (see plot on previous page)

• If we subtract 28.5 dB (found using the scaling factors), the result is -30.5 dB, close to that of the modeled space-based system CNR.

The final question is this: Can we extract a good velocity estimate from a -30 dB signal?

dB 5.280014.0480

5.650

5.69

23

4802

960

505

250

22

2

−≈=×

==

=⎟⎠

⎞⎜⎝

⎛==

===

===

R

AEtot

ground

spaceA

ground

spaceR

ground

spaceE

SSS

S

cmcm

AA

S

kmkm

RR

S

mJmJ

EE

S

Scaling factors (from ground system to Space System)

Parameter Value (ground)

Value (space)

Wavelength (microns) 2.05 2.05

Energy/pulse (mJ) 5 250

System Eff (total) .12 .12

Collector Diam (cm) 9 23

Backscatter 3e-8 3e-8

Transmission 0.92(r.t.) 0.92 (r.t.)

CNRwb @ 2km alt. ?? -29 dB

Noise Bandwidth 50 50


200 400 600 800

-25

-20

-15

-10

-5

0

Range (km)

CNR (dB)



How many photons are needed?

• The number of photons needed is a function of the specification for probability of a good estimate and the degeneracy (photons detected per speckle)

• Optimized system has degeneracy ~1

• The NPOESS system assuming β = 3 x 10-8 (and missing dB are found) has degeneracy ~0.05

• This works out to about 0.5 photons for a 0.5 km height gate or ~60 photons per 120 pulses

• Graph at right indicates that we are in the ballpark, but perhaps a little short, for 50% probability

• Need to demonstrate ground based signal estimate at low degeneracy!

Total photocounts required given degeneracy and specification for fraction of good shots, assuming 1 m/s signal bandwidth and +/- 50 m/s search bandwidth

ParameterNominal

Ground Based System

NPOESS (proposed)

Direct Detect ADM

Wavelength (microns)

0.355 0.355 0.355

Energy/pulse (Joules)

.4 .2 .15

PRF (design) (Hz) 10 100 100

Dwell time (sec) 5 12 7

Collector Diameter (meters)

0.5 1.0 1.5

Stare angle 45 (el) 30 (nadir) 35 (nadir)

Range to 2 km alt.2.8 km (@ 45º el)

830 km @ 30º = ~960km

400 km @ 35º = ~490 km

Scaling factor 2.5×103 1 3.8

# photons @ 2km alt

25.6×106 10000 37600

Minimum standard deviation (300/√N)

0.06 m/s 3 m/s 1.54 m/s

Direct Detection – Space/Ground Inversion

3_

42_

2

105.2

109.3

3438.2

960

24510

12100

450

100

14.

4.

×=

×==

===

=××

==

=⎟⎠

⎞⎜⎝

⎛==

===

−

GS

R

NAESG

ground

spaceR

ground

spaceN

ground

spaceA

ground

spaceE

S

SSSS

S

kmkm

R

RS

sHzsHz

N

NS

cmcm

A

AS

JJ

E

ES

Inversion scaling exampleNPOESS/Ground

0.5 1 1.5 2

x 104

0

1

2

3

4

5

Photo-electrons detected

Minimum

σv

(m/s)

Minimum σv vs. molecular PED - Space Based

1 1.5 2 2.5

x 107

0

0.1

0.2

0.3

0.4

0.5

Photo-electrons detected

Minimum

σv

(m/s)

Minimum σv vs. molecular PED-Ground Based

3_

42_

2

105.2

109.3

3438.2

960

24510

12100

450

100

14.

4.

×=

×==

===

=××

==

=⎟⎠

⎞⎜⎝

⎛==

===

−

GS

R

NAESG

ground

spaceR

ground

spaceN

ground

spaceA

ground

spaceE

S

SSSS

S

kmkm

RR

S

sHzsHz

NN

S

cmcm

AA

S

JJ

EE

S

Inversion scaling exampleNPOESS/Ground


Summary

• Ground-based data sets can be used as a reality check for spacebased lidar performance specifications

• Spacebased systems will likely be “photon starved”, thus demonstrating efficiencies is a key to a successful mission

• HRDL and TODWL data sets are somewhat consistent, and seem to indicate that NPOESS performance (in terms of CNR scaling) within a few dB can be reached (if backscatter coefficients are the same!)

• More estimates at low signal degeneracies are needed to verify velocity estimation capability

• Higher energy lasers may have poorer frequency stability than low energy lasers used in comparisons => more photons needed

• Similarly, direct detection observations with low aperture-energy products are best to simulate space measurements

Scaling Surface and Aircraft Lidar Results for Space-Based Systems (and vice versa) Mike Hardesty,...

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