11/18/02technical interchange meeting progress in fy-02 research rda –capability to collect time...

11/18/02 Technical Interchange Meeting

Progress in FY-02

• Research RDA– Capability to collect time series data– Control of phase shifter

• Phase coding– Sigmet’s implementation of SZ algorithm

– Ground clutter filtering if P1 < P2

– Collected sample time series of SZ coded data


Research RDA Status

• Operational in legacy and RRDA mode• Both modes accommodate RVP-7 in

parallel• RVP-7 used for JPOL demo• Plan to integrate RVP-8 ASAP


RRDA Status• Full control of radar• Integrated with ORPG• Phase shifter control• Versatile VCP structures and tools• Real-time displays• VCP 43 & 44 implemented, data to

ROC• Real-time phase coded acquisition

with first trip decoding


RRDA Status• Staggered PRT capability implemented• Working on real-time software for

staggered PRT• Continuous archive level 1 and 2 for

several hours• Real-time playback of archive data• Data storage in compressed native

format• Matlab format and ingest into Matlab• Recording on tape, CD, and/or DVD


SZ Decoding Algorithms

• Analysis of Sigmet’s SZ decoding algorithm– Sigmet provided internal notes on decoding

algorithm

• Comparison with NSSL’s SZ-1 decoding algorithm– Major difference is in the substitution

method

• MATLAB simulations to compare performance


0 10 20 30 40 50 60 70-8

-6

-4

-2

0

2

4

6

8

p1/p

2 (dB)

err

or

in v

2 est

ima

te (

m s

-1)

(v1-v

2)=-28 to 28 m s-1, w

1=4 m s-1;w

2=4 m s-1

SZ(8/64) code, va=32 m s-1, n

w=0.75, von Hann window

--- mean; ___sd., substitution (Siggia's method)

Sigmet’s Implementation


SZ-1 algorithm

0 10 20 30 40 50 60 70-8

-6

-4

-2

0

2

4

6

8

p1/p

2 (dB)

err

or

in v

2 est

ima

te (

m s

-1)

(v1-v

2)=-28 to 28 m s-1, w

1=4 m s-1;w

2=4 m s-1

SZ(8/64) code, va=32 m s-1, n

w=0.75, von Hann window

--- mean; ___sd., SZ-1 method


0 10 20 30 40 50 60 700

1

2

3

4

5

6

p1/p2 (dB)

sd(v

2) m

s-1

smoothed sd(v2), w

1=4 m s-1, (v

1-v

2)= -28 to +28 m s-1

w2=2 m s-1

w2=4 m s-1

w2=6 m s-1

w2=8 m s-1

2

4

6

8

=10 cm, PRT=0.7812 ms, va=32 m s-1, SZ(8/64) code

SZ-1 methodsubstitution (Siggia's method)

SD(v) for the two methods


SD(σv) for the two methods

0 10 20 30 40 50 60 700

0.5

1

1.5

2

2.5

3

3.5

4

p1/p2 (dB)

sd(w

2) m

s-1

smoothed sd(w2), w

1=4 m s-1, (v

1-v

2)= -28 to +28 m s-1

w2=2 m s-1

w2=4 m s-1

w2=6 m s-1

w2=8 m s-1

2

4

6

8


deconvolution methodsubstitution (Siggia's method)


Bias in σv for the two methods

0 10 20 30 40 50 60 70-6

-5

-4

-3

-2

-1

0

1

2

3

4

p1/p2 (dB)

me

an

err

or

in w

2 est

ima

te (

m s

-1)

smoothed sd(w2), w

1=4 m s-1, (v

1-v

2)= -28 to +28 m s-1

w2=2 m s-1

w2=4 m s-1

w2=6 m s-1

w2=8 m s-1

2

4

6

8


deconvolution methodsubstitution (Siggia's method)


Comparison of Random Phase and SZ code – Lincoln Labs


GCF and Phase Coding

• Optimum ground clutter filter– Frequency response– Notch width

• Ground clutter filtering if P2 > P1

– Sigmet reverts to random phase processing

– SZ algorithm was modified to address this problem


Optimum Clutter Filter

S(v) + NC(v) + N

Noise level: N

N1

v

v

C(v) + N1

GCF(v)

Input

Output

Normalized noise level: 1

v

S(v) + NN


Effects of the number of samples


Optimum filter width

0 0.5 1 1.50

1

2

3

4

5

6

clutter width, c (m s-1)

clu

tter

filte

r h

alf

wid

th,

wcf

/2 (

m s

-1)

CNR= 60

dB

50 dB

40 dB

30 dB

20 dB

10 dB

1.3


Clutter filtering if Pc>P2>P1

1. Re-cohere 1st trip and filter ground clutter

2. Restore lost spectral coefficients of 2nd trip replicas

3. Re-cohere 2nd trip, obtain moments, and filter 2nd trip signal

4. Re-cohere 1st trip and obtain moments


Restoration of lost 2nd trip spectrum replica

1. Use the remaining replicas to determine the magnitude and phase – similar to substitution and works at narrow

widths

2. Reconstruction of magnitudes and phases in case there is only one overlap of the spectral replicas – extends the range of spectrum widths – requires solution of linear equations

(overdetermined system)


GCF effect on 2nd trip spectrum replicas

20 40 60 80 100 120 140 1600

2

4

6

8

10

a

b

so(i)

ma

gn

itud

espectrum of 2nd trip echo

va=32 m s-1, v=-22 m s-1, w=2 m s-1, M=160

20 40 60 80 100 120 140 1600

1

2

3

4

5

s(k)

ma

gn

itud

e

SZ(8/64) phase coded spectrum

GCF GCF

8

1

2

3

4

5

6

7


P2/P1 Ratio for which spectral moments of 1st trip can be recovered

0 1 2 3 4 5 60

10

20

30

40

50

60

spectrum width, w2 (m s-1)

ove

rlay

po

we

r ra

tio, p

2/ p1 (

dB

)w

1=4m s-1, SNR

1=20dB, CNR=70dB

va=32m s-1, w

c=0.28m s-1, M=64, n

c=15

performance of the 2nd trip signal restoration schemes -1 & 2

(a)

(b)

(c)

(a) - no restoration(b) - scheme-1(c) - scheme-2

p1

v1

w1


Data Collection

• Volume Coverage Pattern Definitions– ROC requested non-standard VCPs– Modified RRDA VCP definitions to accommodate

new requirements• Automatic switch between phase-coded and non-

phase-coded elevation cuts• Staggered PRT

• Level-1 Data Archiving– Expanded data headers to include new metadata– Currently support MATLAB and RRDA internal

formats


Collection of SZ coded data

Reflectivity field

PRT #1T = 3.1 msra = 466 km

vNYQ = 8.92 m s-1


Collection of SZ coded data

Doppler velocity field

PRT #1T = 3.1 msra = 466 km

vNYQ = 9 m s-1


Real-time decoding of 1st trip

PRT #4 (T = 1.17 ms)ra = 175 km

vNYQ = 24 m s-1

PRT #8 (T = 0.78 ms)ra = 117 km

vNYQ = 35 m s-1


Plans

• Real-time implementation of SZ

algorithm

• Real-time implementation of

Staggered PRT

• SPS Simulator

• Oversampling and Whitening in range


SPS Simulator

• R/V algorithms require development at the RDA DSP level – Rapid algorithm prototyping and validation– Data visualization tools– Off-line development using Archive 1 data

• Working on simulation of RRDA DSP (Legacy WSR-88D HSP/PSP) using MATLAB– Capability to simulate RVP-8


Plans for the SPS Simulator

• Data Analysis– Spectral analysis

• Data Processing– R/V ambiguitiy mitigation

• Phase coding • Staggered PRT

– Interaction with other techniques• Oversampling and whitening in range


Oversampling of Weather Echoes in Range

L samples within the pulse


Whitening-Transformation-Based Estimates

• Oversample in range by a factor of L– Range samples are correlated– Correlation is known assuming uniform reflectivity

• Decorrelate oversampled range data– Whitening transformation is derived from “known” C– Works for SNR > 15 dB

• Compute autocovariances for each range gate• Average autocovariances from L range gates

– Statistical errors are reduced


Reduction in statistical errors by processing oversampled signals in range

PRT = 3 ms M = 32 L = 9

NEXRAD specification


Plans for Oversampling and Whitening in Range

• Collection of oversampled data with RRDA– Long pulse, L = 3– Digital receiver, L ≥ 5– Examine RVP-8 capabilities

• Statistical analysis– Matched filter, Regular averaging, Whitening

• Visual comparison of PPI displays • Effects of reflectivity gradients• Pseudo-whitening techniques

11/18/02technical interchange meeting progress in fy-02 research rda –capability to collect time...

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