Technical Interchange Meeting

Spring 2008: Status and Accomplishments

TASKS

• Task 1. Support Deployment of SZ-2 RV Ambiguity Mitigation Algorithms– To support the ROC in upgrading the SZ-2 RV

Ambiguity Mitigation algorithm – To discuss any anomalies in the SZ-2

algorithm encountered by the ROC at operational sites

TASKS

• Task 2. Support implementation of Staggered PRT – Determine operational scanning strategy and if any

additional PRFs are required – Update AEL to allow any PRT ratio – Analyze other PRT ratios– Support implementation of the Clutter Spectrum Filter– Support validation and verification of Staggered PRT

Clutter Spectrum Filter

• Task 3. Spectrum width improvements – Provide an algorithm that includes the spectrum width

improvements

TASKS

• Task 4. Spectral Processing – Provide information on NSSL’s spectral

processing• Spectral processing for dual polarization variables

(Bachmann and Zrnic paper, and Bachmann’s PhD) • Ground clutter identification using Polarimetric Spectral

densities (Melnikov and Zrnic paper Radar Conf. Australia and report to be put on NSSL’s WEB)

Polarimetric Spectral Density of ZDR

Polarimetric Spectral Analysis

• Spectral Density of Differential Reflectivity SDR (vk) = |Ah(vk)|2 /|Av(vk)|2

• Spectral Density of Differential Phase

SDP(vk) = arg{Ah*(vk)Av(vk)}

• Spectral Density of Cross Correlation Coefficient Sρhv(vk) = Running sum product of three spectral coefficients

-30 -20 -10 0 10 20 30-10

-5

0

5

10

15

20

Z DR (

dB)

-30 -20 -10 0 10 20 300

0.2

0.4

0.6

0.8

1

hv

-30 -20 -10 0 10 20 30

-100

0

100

Velocity (m s-1)

(

o )

-20 0 20

0

20

40

Velocity, m s-1

Pow

er,

dB

@ 30 km

-20 0 20

0

20

40

Velocity, m s-1

Pow

er,

dB

@ 40 km

-20 0 20

0

20

40

Velocity, m s-1

Pow

er,

dB

from 30 to 35 km

-20 0 20

0

20

40

Velocity, m s-1

Pow

er,

dB

from 40 to 45 km

H

V

H

V

H

V

H

V

Spectral density of ZDR

Spectral density of ρhv

Spectral densities of Powersi.e., Doppler Spectra

Densities are medians from 20 rangelocations, 30 to 35 km

Histograms of PolVariables from

weather and clutter

Histogramsof pol varobtained from full spectra and from 3 linescentered on 0Doppler

Cold Season Warm Season

Adaptive Clutter Recognition Criterion

-Compute the polarimetric variables, ZDR, ρhv, andδ from the spectra at and near zero Doppler

-For SNR>3 dB:

Declare clutter

If {(ZDR < -2 dB) OR (ZDR > 5 dB) OR (|ρhv|<0.8) OR (δ > 20o)}

Otherwise it is not clutter

Adaptive Generation of Clutter Map using Dual Polarization Spectra of ground clutter and weather at Horizontal and Vertical polarization

Notch filter Filtered spectra for the decision

AP cases

a) Sep 2007c) Oct 2007

HHistogramsSep 2007 case

Clutter identified with the algorithm(red) in a field of weather echoes (aqua marine)

Distribution of Clutter to Noise Ratio in the H and V channels

GMAPapplied independentlyeverywhereto H and Vchannels

Adaptive GMAP applied equally toboth channelsaccording tothe spectralrecognition(Serbianoven bakedbread) algacting on the H channel

Probability of Detection

Performance

• Simulations– Add time series data from clutter and weather

and apply the classification criterion

• Probability of false alarm ~ 5%

• Probability of detection ~ 90 %

• Addition of coherency threshold (NCAR) could improve the performance?

Polarimetric Spectral Analysis Separates Insects from BirdsBachmann and Zrnic 2007Bachmann’s PhD (NSSL,WEB)

10 20 30 40 50 60 70 80 90 100 110

-60

-40

-20

0

20

Range, km

Pow

er,

dB

0.5o

6.0o

Radial @ 180 - power spectral density

10 20 30 40 50 60 70 80 90 100 110

-60

-40

-20

0

20

Range, km

Powe

r, dB

0.5o

6.0o

Range, km

Pow

er, d

B

Power along the radial

0 20 40 60 80 100Range, km

35

0

-35

Vel

ocity

, m s

–1

Power spectral density field Power, dB

-20 0 20

-60

-40

-20

0

H-channel spectra @ range 30km

Velocity, m s-1

Pow

er, d

B

-20 0 20

-60

-40

-20

0

V-channel spectra @ range 30km

Velocity, m s-1

Pow

er, d

B

Spectral density of , Zdr, Average spectral densities for ranges from 30 to 70 km for each radial of PPI to get Spectral VADs

Vel

ocity

, m

s-1

exp.21,el. 0.5, range from 30 km to 70 km

50 100 150 200 250 300 350

35

0

-35-35-30-25

-20-15

Vel

ocity

, m

s-1

50 100 150 200 250 300 350

35

0

-35

0.6

0.7

0.8

0.9

Vel

ocity

, m

s-1

50 100 150 200 250 300 350

35

0

-35

0

5

10

Vel

ocity

, m

s-1

50 100 150 200 250 300 350

35

0

-35

-100

0

100

Azimuth, degree

N NE E SE S SW W NW N

Insects

Birds

Power, dB

Zdr, dB

, degree

Polarimetric Sea Clutter Algorithm (Ryzhkov et al. paper)

• This is Spring bonus

• Fuzzy logic algorithm uses: SD(P), SD(ΦDP), LDR, ZDR, ρhv, and V

• Tested on SPOL data from 2001 (Washington coast)

Sca

tterg

ram

s