KSRBL Science Colloquium 2009 Aug 24 1 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

KSRBL Science Colloquium 2009 Aug 24 2 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

KSRBL Science Colloquium 2009 Aug 24 3 KSRBL Antenna Full Sun coverage => 2.1 m antenna Gives 33 arcmin at 18 GHz Yagi Feed (245 and 410 MHz) Spiral Feed (0.5-1 GHz)

KSRBL Science Colloquium 2009 Aug 24 4 Frequency Coverage Frequency range  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

KSRBL Science Colloquium 2009 Aug 24 5 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).

KSRBL Science Colloquium 2009 Aug 24 6 RFI Excision (this is a portion of a single band at full resolution)

KSRBL Science Colloquium 2009 Aug 24 7 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?.

KSRBL Science Colloquium 2009 Aug 24 8 Example: Gyrosynchrotron Spectrum Pk 1: B t = 120 G Pk 2: B t = 60 G Pk 1: B = 240 G Pk 2: B = 120 G

KSRBL Science Colloquium 2009 Aug 24 9 Example: High-Resolution Bursts Decimetric burst types, seen with similar frequency and time resolution as KSRBL

KSRBL Science Colloquium 2009 Aug 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? possible concern? alert!

KSRBL Science Colloquium 2009 Aug Burst Location

KSRBL Science Colloquium 2009 Aug Board Implementation CASPER iBOB-based 500 MHz Spectrometer  2048 channels, 4 tap PFB (polyphase filter bank)  Accumulates power (S 1 ) and power- squared (S 2 ). 1 GS/s (1 GHz clock), MHz IF Settable dump times—use 25 ms Output via fast-ethernet Operate 4 boards in parallel, for 2 GHz total bandwidth ADC FPGA

KSRBL Science Colloquium 2009 Aug Simplified Block Diagram Multiple levels of scaling to ensure sufficient precision of P and P 2. ADC 4096-pt FFT P Multiplier P 2 P RAM Serializer P 2 Accumulator P RAM Parallel- izer P 2 Bit select RF In 1 GHz clock Scale bit shift scale coeff bit select P 2 bit select accum length P bit select BRAM P P2P2 Data Out (ethernet) PFB

KSRBL Science Colloquium 2009 Aug 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

KSRBL Science Colloquium 2009 Aug 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

KSRBL Science Colloquium 2009 Aug Example: A Band with No RFI One instantaneous (25 ms) spectrum with no RFI Each spectral point is an accumulation of M = 6104 samples. SK (=1 ±  ) Occasionally (~0.13% of time) exceeds 3  threshold

KSRBL Science Colloquium 2009 Aug Plot of SK vs spectral power ( S 1 ) (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.

KSRBL Science Colloquium 2009 Aug Full-Resolution vs. Integrated Spectrum Average spectrum (3-3.5 GHz) Full-resolution dynamic spectrum (2048 spectral channels) Same spectrum after applying SK flags (2048 spectral channels) Clean spectrum after frequency-binning to target resolution (512 spectral channels)

KSRBL Science Colloquium 2009 Aug 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

KSRBL Science Colloquium 2009 Aug A Key Plot for Understanding SK Armed with these ideas, let’s look at bands with RFI

KSRBL Science Colloquium 2009 Aug Example—A Band with a Lot of RFI Average spectrum (0.5-1 GHz) Full-resolution dynamic spectrum (2048 spectral channels) Same spectrum after applying SK flags (2048 spectral channels) Clean spectrum after frequency-binning to target resolution (512 spectral channels) Average of 150 spectra, each accumulated with M = 6104 samples.

KSRBL Science Colloquium 2009 Aug Why does this RFI survive? Previous plot was lower resolution than actual data. Zoom in at full resolution

KSRBL Science Colloquium 2009 Aug SK Estimator vs. Spectral Power SK mimics Gaussian noise! SK > 1  highly intermittent SK < 1  more continuous

KSRBL Science Colloquium 2009 Aug 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.

KSRBL Science Colloquium 2009 Aug This RFI is untouched! Incompletely removed Turns out this is XM and Sirius (digital satellite radio)

KSRBL Science Colloquium 2009 Aug % duty cycle Digital radio acts like Gaussian noise SK Estimator vs. Spectral Power

KSRBL Science Colloquium 2009 Aug Southern California Edison digital data link

KSRBL Science Colloquium 2009 Aug Digital data links act like Gaussian noise 6093 MHz center frequency 30 MHz BW, pointing right at observatory. SK Estimator vs. Spectral Power

KSRBL Science Colloquium 2009 Aug Multiscale SK

KSRBL Science Colloquium 2009 Aug SRB Effects on Navigation System 30 s near end of burst System automatically switches between polarizations Observed by OVSA and FST at 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 GHz

KSRBL Science Colloquium 2009 Aug 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.

KSRBL Science Colloquium 2009 Aug 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.

KSRBL Science Colloquium 2009 Aug 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. S 1 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.

KSRBL Science Colloquium 2009 Aug Thank You

KSRBL Science Colloquium 2009 Aug Effect of Incorrect Precision When S 1 ( S 2 ) precision is too low (LSB truncated), the effect is to raise (lower) the SK estimator S1 truncated slightly (SK raised to 1.014) Excessive clipping of valid data

KSRBL Science Colloquium 2009 Aug Results in too many flagged points Mean of SK estimator in this case is due to truncation of S 1. Thus, it is important to manage dynamic range using settable parameters.

KSRBL Science Colloquium 2009 Aug Simplified Block Diagram Multiple levels of scaling to ensure sufficient precision of P and P 2. ADC 4096-pt FFT P Multiplier P 2 P RAM Serializer P 2 Accumulator P RAM Parallel- izer P 2 Bit select RF In 1 GHz clock Scale bit shift scale coeff bit select P 2 bit select accum length P bit select BRAM P P2P2 Data Out (ethernet) PFB