1. Solar Probe Plus FIELDS RFS Peter R. Harvey

2. RFS FSW Requirements

3. Processing Baseline Cycle = 2^N (==8 def.) DCB Seconds – Burst goes as fast as possible. – Cal and Engineering are special cases Modes – [a] BasicSurvey, [b] DirectionFinding, [c] BurstMode, – [d] Calibration, and [e] Engineering (Raw waveforms). Single Channel Pair Focus – “M” Spectra accumulated as rapidly as possible (9 to 15) – Data Buffered in SRAM until processed  Single Gain in an averaging period Processing

4. Modes

5. Initialization FSW Initialization of PFB 1.Select EEPROM PFB table. 2.Copy ½ waveform (16k integers) 3.Reverse waveform 4.EEPROM required : 32 KB Only a Single Array Required in Memory

6. Initialization FSW Initialization of Sine Table 1.Select EEPROM Sine table. 2.Build Full Sine table in RFS memory a)Copy ¼ wave b)Reverse ¼ wave 3.EEPROM required : 2 KB (1K points)

7. Sampling RFS SRAM 1.Sine Table 2.PFB Table 3.Space for 15 Waveform pairs

8. Processing FPGA Processing Step 1. Collect N waves in M tries If over range, repeat at low gain Step 2. PFB&FFT process N waves a.Control FPGA, get spectra b.Reduce Spectra to ~64 bins c. Store Reduced Spectra FSW Processing Step 1. Reject Min/Max Spectra 1 or 2 rounds Step 2. Sum 5 to 7 Reduced Spectra Step 3. Compute Auto1,2 and Cross Step 4. Compute Phase & Coherence Step 5. Computes offsets for X1,X2

9. Processing

10. Compression Float to 16-bit trade options Numeric Analyses/Performance Working with Simulated Spectra 7.5 Orders of magnitude signal ~ 1 in gain circuitry Leaves ~ 6+ orders of magnitude 24-bit raw spectra (16 million) Output Spectra = (R 2 + i 2 ) = 49 bits Double Prec. FP has 53-bit mantissa Measured 50 pt power spectra takes 4.4 ms SRAM can hold 9 x 2 waveforms

11. Plasma Tracking Using Spectra Data  On Bepi-Columbo, used a simple “first peak” algorithm. Positive going peak.  Logic (discussed in Meudon):  [1] Use a 40 bin window to average for 10 spectra then look for the peak in that window; if there is no peak, go to [2].  [2] Use the last full 2048 point spectra to find a peak.  [3] Telemeter 20 points centered on the peak Plasma Tracking Using Other Data Sources  Useful when at Solar Distance > 0.125 AU (TBD)  FSW Should Predict Plasma Frequency Multiple Ways:  Model of Plasma Frequency[Solar Distance]  SWEAP Cup Flux  SWEAP ESA Ion Flux  Model of Plasma Freq [S/C Potential]. S/CPot = -(V1+V2+V3+V4)/4 Plasma Tracking

12. Plasma Frequency Determination 1.Difficult to use LFR spectra 2.Not a smooth curve 3.Moving average

13. Diagnostic Support to FPGA & FSW Verification  Generate/Load Sine Waves into the RFS Waveform Memory  Generate/Load Dust Points on top of RFS Waveform Memory  Dump RFS Waveform Memory  Dump Full 4096 Spectra  Generate/Load Spectra into the DCB RFS Buffers Diagnostic Support to Flight  Find Dust Impacts and Playback only those points. (If we can get a picture of the dust impacts on the sensor measurements, we would have a better change of developing a software “dust cleaning” algorithm. Diagnostics

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15. APID 2B1 HFR Spectra

16. APID 2B2 LFR Spectra

17. APID 2B3 RFS Waveform

18. Issues Dust Detection  On STEREO, common to get 50 dust hits per second. (Sometimes max rate of over 6000/second!) 50/second = 20 msec per hit.  In 0.8 msec x 10 samples = 8 msec, we have a good chance to get clean spectra with software filtering  In 8msec x 10 samples = 80 msec, probably going to get hit 4 times. Issues

19. Backup Issues

20. Math