science with the korean solar radio burst locator (ksrbl)

KSRBL Science Colloquium2009 Aug 24

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Science with the Korean Solar Radio Burst Locator (KSRBL)

Dale E. Gary & Gelu M. Nita

Center for Solar-Terrestrial Research

New Jersey Institute of Technology


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Outline• Overview of KSRBL

• Topics for Study Radio spectrum for study of solar activity Burst location Radio frequency interference mitigation Radio effects on navigation and

communication systems

• Conclusions


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KSRBL AntennaFull Sun coverage

=> 2.1 m antenna

DFWHM

22.1

Gives 33 arcmin at 18 GHz

Yagi Feed (245 and 410 MHz)

Spiral Feed (0.5-1 GHz)


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Frequency Coverage• Frequency range

0.5-18 GHz continuous coverage, plus 245 and 410 MHz (yagi feed)

• Frequency resolution Best resolution 244 kHz (for RFI excision) Target science resolution 1 MHz (4:1

compression)

• Instantaneous bandwidth 4 x 500 MHz = 2 GHz

17,500 frequency points at 1 MHz resolution


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Time Resolution• Full spectrum in 1 s• Time resolution for each sample is 25 ms,

measured four times before tuning (100 ms for each tuning). - + + + - + + +

• Takes 10 tunings to cover 18 GHz, hence 1 s to cover all bands.

• Best resolution on a single band, nominally 25 ms, but can be changed (trade-off with data-rate and data volume).


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RFI Excision(this is a portionof a single bandat full resolution)


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Solar Radio Burst (SRB) Spectra• The spectrum of SRBs reveals a great deal of

information about plasma parameters (temperature, density, magnetic field strength, accelerated electron energy distribution). KSRBL is unique in its ability to combine high frequency resolution with broad frequency coverage.

• At very high temporal and spectral resolution, additional features may appear, especially at decimetric (<3 GHz) frequencies.

• Polarization is also important—KSRBL measures only RCP (required for burst location). A measurement of LCP is also needed—a second KSRBL?.


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Example: Gyrosynchrotron Spectrum

Pk 1: Bt = 120 GPk 2: Bt = 60 G

Pk 1: B = 240 GPk 2: B = 120 G


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Example: High-Resolution Bursts

• Decimetric burst types, seen with similar frequency and time resolution as KSRBL


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Burst Location• Motivation

Because of Parker spiral, particles from bursts east of central meridian are few and of low energy.

Particles from bursts on the west limb are of far more concern. Knowing the location of the burst on the disk, especially for large

flares, is important. KSRBL can act as backup for spacecraft.

safe?possibleconcern?

alert!


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Burst Location


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Board Implementation• CASPER iBOB-based 500 MHz

Spectrometer 2048 channels, 4 tap PFB

(polyphase filter bank) Accumulates power (S1) and power-

squared (S2).• 1 GS/s (1 GHz clock), 500-1000

MHz IF• Settable dump times—use 25 ms • Output via fast-ethernet• Operate 4 boards in parallel, for

2 GHz total bandwidth

ADC

FPGA


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Simplified Block Diagram• Multiple levels of scaling to ensure sufficient

precision of P and P2.

ADC4096-pt

FFT

P

Multiplier P2

P

P

RAM Serializer

P2

Accumulator

P

RAM Parallel-

izer P2

Bit select

Bit select

RF In

1 GHzclock

Scale

bitshift

scalecoeff

bitselect

P2 bitselect

accumlength

P bitselect

BRAM

P

P2

Data Out(ethernet)

PFB


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• We have described the SK Algorithm previously (Nita et al. 2007, PASP 119, 805). The SK estimator provides a way to distinguish whether a single accumulation (time-frequency bin) is consistent with Gaussian noise.

• Bins with certain kinds of radio frequency interference (RFI) are typically not Gaussian, hence the SK estimator can be used to identify and flag bins containing such RFI.

Spectral Kurtosis RFI Algorithm


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• The recipe for computing the SK estimator is very simple, and lends itself to real-time RFI excision using high-speed digital processing. To compute the SK estimator, one must accumulate sums of power and power-squared

• The SK estimator for an accumulation over M samples is then

• The variance of the SK estimator is so with a criterion of an accumulation in spectral channel k is Gaussian if it obeys the expression

Spectral Kurtosis RFI Algorithm

M

m

M

mmkmk kPSPS

1 1

2,2,1 channelfrequency ; ;

2 22

1

1 ( 1 for Gaussian noise)1k

SMV M

M S

2 41 3 .kV

M

4 / ,M 3 ,


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Example: A Band with No RFIOne instantaneous (25 ms) spectrum with no RFI

Each spectral point is an accumulation of M = 6104 samples.

1 6 / M

1 6 / MSK (=1±)

Occasionally (~0.13% of time) exceeds 3 threshold


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Plot of SK vs spectral power (S1)(very useful plot, as we will see)

Shows that SK estimator is independent of power level—a key property.

SK Estimator vs. Spectral Power

SK estimator for 150 instantaneous spectra

Also, RFI decision is made based on statistics of a single accumulation of a single spectral channel. No “relative” comparisons needed.


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Full-Resolution vs. Integrated Spectrum

Average spectrum(3-3.5 GHz)

Full-resolutiondynamic spectrum

(2048 spectral channels)

Same spectrum after applying SK flags


Clean spectrum after frequency-binning to

target resolution(512 spectral channels)


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SK Estimator for Non-Gaussian Signals• The SK estimator for a Gaussian signal is very close to 1, but what is

the SK value for non-Gaussian signals?• One type of RFI we have simulated is a CW signal of constant

amplitude, which can be used to simulate transient RFI by considering its presence or absence with some duty cycle, d.

• Consider M contiguous samples out of which only R are contaminated by RFI of signal to noise ratio k. This leads to an RFI duty cycle of d = R/M. For this case, the expected SK estimator value is

• Note several interesting properties: For d = ½, (50% duty cycle), the estimator is always 1 For d < ½ (highly intermittent RFI), the estimator is above 1 For d > ½ (more continuous RFI), the estimator is below 1

2

22

)/1(

)2/1(1

1 k

kk d

d

M

MV


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A Key Plot for Understanding SK

Armed with these ideas, let’s look at bands with RFI


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Example—A Band with a Lot of RFI

Average spectrum(0.5-1 GHz)

Full-resolutiondynamic spectrum


Same spectrum after applying SK flags


Clean spectrum after frequency-binning to

target resolution(512 spectral channels)

Average of 150 spectra, each accumulated with M = 6104 samples.


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Why does thisRFI survive?

Previous plot was lower resolution than actual data.

Zoom in at full resolution


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SK mimicsGaussian

noise!SK > 1 highly

intermittent

SK < 1 more

continuous


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SK vs. Power Plot Features• Continuous RFI appears as discrete dots.• Intermittent RFI appears as “fountain” of points.• Curve of fountain likely reflects effective duty-

cycle. “Accidental” 50% duty cycle can occur.• Multiscale SK moves points—can guard against

50% duty cycle problem.• Some RFI masquerades as Gaussian noise.• Let’s take a closer look to discover what

characteristics the problem-RFI has.


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This RFI isuntouched!

Incompletelyremoved

Turns out this isXM and Sirius

(digital satellite radio)


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50% dutycycle

Digital radio actslike Gaussian noise



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Southern California Edisondigital data link


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Digital data links actlike Gaussian noise 6093 MHz center frequency

30 MHz BW, pointingright at observatory.



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Multiscale SK


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SRB Effects on Navigation System

30 s near end of burst

System automatically switches between polarizations

Observed by OVSA and FSTat Owens Valley Solar Observatory

OVSA and FST data of this record solar burst. Zooming in reveals the burst as composed of millions of millisecond spike bursts (electron-cyclotron maser emission). The FST data at right shows 20 ms time-resolution data, switching between right-circular (RCP) and left-circular polarization (LCP) every 4 s. The spikes are essentially 100% RCP.

18

10

1

GH

z


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GPS Outage• GPS satellites broadcast at 1247

and 1575 MHz, and the signal is right-circularly polarized (RCP).

• The burst reached record flux levels at both of these frequencies, and was also RCP.

• The direct interference of the solar flux caused receivers on Earth to loose lock on the satellites.


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Conclusion• KSRBL is a unique instrument in its combination

of high frequency and time resolution and broad frequency coverage.

• It is a research instrument ideal for four types of study: Solar radio bursts and solar activity Burst location and space weather effects Radio frequency interference mitigation SRB effects on navigation and communication

systems.


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Conclusions Re: RFI• KSRBL has the first FPGA implementation of Spectral

Kurtosis for real-time flagging of RFI.• The method supplies an automatic way to flag the worst

intermittent RFI.• The SK estimator vs. S1 plot is useful for characterizing

types of RFI: SK < 1 is intermittent RFI, easy to remove. A few points may get

through by chance hitting near 50% duty cycle. Typical continuous RFI appears as small clusters, sometimes

near or overlapping with SK = 1 window. Multiscale SK can be applied to address this.

Digital radio, digital data links, and likely digital TV are “awful”—they are both band-filling and they appear to the SK algorithm as indistinguishable from Gaussian noise.

• Further study of digital RFI is needed.


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Thank You


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Effect of Incorrect Precision • When S1 (S2) precision is too low (LSB truncated), the effect is to raise

(lower) the SK estimator 2 22

1

11k

SMV M

M S

S1 truncated slightly (SK raised to 1.014)

Excessive clipping ofvalid data


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Results in too many flagged points

Mean of SK estimator in this case is 1.014 due to truncation of S1.

Thus, it is important to manage dynamic range using settable parameters.


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Simplified Block Diagram• Multiple levels of scaling to ensure sufficient

precision of P and P2.

ADC4096-pt

FFT

P

Multiplier P2

P

P

RAM Serializer

P2

Accumulator

P

RAM Parallel-

izer P2

Bit select

Bit select

RF In

1 GHzclock

Scale

bitshift

scalecoeff

bitselect

P2 bitselect

accumlength

P bitselect

BRAM

P

P2

Data Out(ethernet)

PFB

science with the korean solar radio burst locator (ksrbl)

Documents

high frequency resolution

stime resolution

spectral resolution

similar frequency

sk estimator

broad frequency coverage

study radio spectrum

ms output