Boonton 4240 RF Power Meter - Manual (Page 118)

Boonton 4240 Series RF Power Meter
Step 6: The Sensor Temperature Drift Error depends on how far the temperature has drifted from the sensor calibration
mperature, and the temperature coefficient of the sensor. In this example, an AutoCal has just been performed on the
nsor, and the temperature has not drifted at all, so we can assume a value of zero for sensor temperature drift uncertainty.
U
SnsrTempDrift
= ± 0.0 %
tep 7: This is a relatively low-level measurement, so the noise contribution of the sensor must be included in the uncertainty
alculations. We’ll assume default filtering. The signal level is -55dBm, or 3.16nW. The RMS noise specification for the
1075 sensor is 30pW, from the sensor’s datasheet. Noise uncertainty is the ratio of these two figures.
U
Noise Error
= ± (Sensor Noise (in watts) / Signal Power (in watts)) × 100%
= ± (30.0e-12 / 3.16e-9) × 100 %
= ± 0.95%
Step 8: The Sensor Zero Drift calculation is very similar to the noise calculation. For sensor zero drift, the datasheet
specification for the 51075 sensor is 100pW, so we’ll take the liberty of cutting this in half to 50pW, since we just performed
an AutoCal, and it’s likely that the sensor hasn’t drifted much.
U
Zero Drift
= ± (Sensor Zero Drift (in watts) / Signal Power (in watts)) × 100%
= ± (50.0e-12 / 3.16e-9) × 100 %
= ± 1.58%
9: The Sensor Calfactor Uncertainty is calculated from the uncertainty values in the Boonton Electronics Power Sensor
anual. There is no entry for 10.3GHz, so we’ll have to look at the two closest entries. At 10GHz, the calfactor uncertainty
4.0%, and at 11GHz it is 4.3%. These two values are fairly close, so we’ll perform a linear interpolation to estimate the
uncertainty at 10.3GHz:
U
CalFactor
= [ ( F - F1 ) * (( CF2 - CF1 ) / ( F2 - F1 )) ] + CF1
= [ ( 10.3 - 10.0 ) * (( 4.3 - 4.0 ) / ( 11.0 - 10.0 )) ] + 4.0
= 4.09%
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Application Notes
6-10