Boonton 4530 Peak Power Meter User Manual - Manual (Page 159)

Boonton Electronics Chapter 5
4530 Series RF Power Meter Making Measurements
5-17
Sensor Noise. The noise contribution to pulse measurements depends on the number of samples averaged
to produce the power reading, which is set by the “averaging” menu setting. For continuous measurements
with CW sensors, or peak sensors in modulated mode, it depends on the integration time of the measurement,
which is set by the “filter” menu setting. In general, increasing filtering or averaging reduces measurement
noise. Sensor noise is typically expressed as an absolute power level. The uncertainty due to noise depends
upon the ratio of the noise to the signal power being measured. The following expression is used to calculate
uncertainty due to noise:
Noise Error = ± Sensor Noise (in watts) / Signal Power (in watts)
0 100 %
The noise rating of a particular power sensor may be found on the sensor datasheet, or the Boonton Electronics
Power Sensor Manual. It may be necessary to adjust the sensor noise for more or less filtering or averaging,
depending upon the application. As a general rule (within a decade of the datasheet point), noise is inversely
proportional to the filter time or averaging used. Noise error is usually insignificant when measuring at high
levels (25dB or more above the sensor’s minimum power rating).
Sensor Zero Drift. Zero drift is the long-term change in the zero-power reading that is not a random, noise
component. Increasing filter or averaging will not reduce zero drift. For low-level measurements, this can be
controlled by zeroing the meter just before performing the measurement. Zero drift is typically expressed as
an absolute power level, and its error contribution may be calculated with the following formula:
Zero Drift Error = ± Sensor Zero Drift (in watts) / Signal Power (in watts)
0 100 %
The zero drift rating of a particular power sensor may be found on the sensor datasheet, or the Boonton
Electronics Power Sensor Manual. Zero drift error is usually insignificant when measuring at high levels
(25dB or more above the sensor’s minimum power rating). The drift specification usually indicates a time
interval such as one hour. If the time since performing a sensor Zero or AutoCal is very short, the zero drift is
greatly reduced.
Sensor Calibration Factor Uncertainty. Sensor frequency calibration factors (“calfactors”) are used to
correct for sensor frequency response deviations. These calfactors are characterized during factory calibration
of each sensor by measuring its output at a series of test frequencies spanning its full operating range, and
storing the ratio of the actual applied power to the measured power at each frequency. This ratio is called a
calfactor. During measurement operation, the power reading is multiplied by the calfactor for the current
measurement frequency to correct the reading for a flat response.
The sensor calfactor uncertainty is due to uncertainties encountered while performing this frequency calibration
(due to both standards uncertainty, and measurement uncertainty), and is different for each frequency. Both
worst case and RSS uncertainties are provided for the frequency range covered by each sensor, and are listed
on the sensor datasheet and in the Boonton Electronics Power Sensor Manual.
If the measurement frequency is between sensor calfactor entries, the most conservative approach is to use
the higher of the two corresponding uncertainty figures. It is also be possible to estimate the figure by linear
interpolation.
If the measurement frequency is identical to the AutoCal frequency, a calfactor uncertainty of zero should be
used, since any absolute error in the calfactor cancels out during AutoCal. At frequencies that are close to the
AutoCal frequency, the calfactor uncertainty is only partially cancelled out during AutoCal, so it is generally
acceptable to take the uncertainty for the next closest frequency, and scale it down.