Time correction with pps signal disciplined by gps receiver
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Time Correction with PPS Signal Disciplined by GPS Receiver. Paolo Zoccarato, Tommaso Occhipinti, Ivan Capraro, Pietro Bolli, Filippo Messina, Massimiliano Belluso. PPS data analysis. Counts of the pps signal. Mini -T Trimple specification :. PPS acquired during Feige observation.

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Time Correction with PPS Signal Disciplined by GPS Receiver

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Time correction with pps signal disciplined by gps receiver

Time Correction with PPS Signal Disciplined by GPS Receiver

Paolo Zoccarato, Tommaso Occhipinti,

Ivan Capraro, Pietro Bolli, Filippo Messina, Massimiliano Belluso


Pps data analysis

PPS data analysis

Counts of the pps signal

Mini-T Trimple

specification:

PPS acquired during

Feige observation

Counts differences of the pps signal

About 600 counts, i.e. ~15 ns

About 2150 counts, i.e. ~ 54 ns


Estimation of the initial reference period

Estimation of the initial reference period

Fit curve equation:

Removing the linear and

quadratic terms we obtain:

670 counts

On average there is a 1 pps

every 40959748112.9816 counts,

then the real length of the

TDC initial reference period is:


Pps time

PPS time

The estimation error is about

137 counts, i.e. ~3.4 ns

Determined the real initial reference period we

convert the counts in time:

Now we must remove the residual error

respect to the ideal time due to

the oscillator drift and offset


Oscillator parameters estimation

Oscillator parameters estimation

The fit curve equation is:

The fit error is about 360 ns:

Removing the oscillator offset and drift

we obtain the stochastic residual of the

oscillator:

The estimated initial error phase,

offset and drift coefficients

can be used to correct the time tags of Feige.


Oscillators stochastic noise

Oscillators stochastic noise

The stochastic residuals are on the order of 10-6 [sec], according with the values of a quartz oscillator.

The residual noise is a flicker phase noise (see figure above), the predominant noise on the Quartz oscillators in the short period, as it is possible to see in the table at the right.

W = white, F = flicker, RW = random walk,

FM = frequency modulation, PM = phase modulation


Crab analysis

Crab analysis

  • We have realized two Matlab functions to correct the time tags.

  • To correct the Crab data we don’t have the pps data, so we used pps data acquired during Feige Observation

  • The period of the Crab without this correction is 30.61 ms, while with the correction is 33.61 ms.

  • Crab period became very close to its real period (33.71 ms).


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