Boonton 4530 Peak Power Meter User Manual User Manual
Page 161
Boonton Electronics
Chapter 5
4530 Series RF Power Meter
Making Measurements
5-19
sensor, 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 %
Step 7: This is a relatively low-level measurement, so the noise contribution of the sensor must be included in the
uncertainty calculations. We’ll assume default filtering. The signal level is -55dBm, or 3.16nW. The RMS noise
specification for the 51075 sensor is 30pW, from the sensor’s datasheet. Noise uncertainty is the ratio of these two
figures.
U
NoiseError
= ± Sensor Noise (in watts) / Signal Power (in watts)
= ±30.0e-12 / 3.16e-9
0 100 %
= ±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
ZeroDrift
= ± Sensor Zero Drift (in watts) / Signal Power (in watts)
= ±50.0e-12 / 3.16e-9
0 100 %
= ±1.58%
Step 9: The Sensor Calfactor Uncertainty is calculated from the uncertainty values in the Boonton Electronics Power
Sensor Manual. There is no entry for 10.3GHz, so we’ll have to look at the two closest entries. At 10GHz, the calfactor
uncertainty is 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%
Step 10: Now that each of the individual uncertainty terms has been determined, we can combine them to calculate the
worst-case and RSS uncertainty values:
U (±%)
K
(U
0
K)
2
( %
2
)
1.
instrument uncertainty
0.10
0.500
0.0025
2.
calibrator level uncertainty
2.45
0.577
1.9984
3.
calibrator mismatch uncertainty
0.34
0.707
0.0578
4.
source mismatch uncertainty
6.68
0.707
22.305
5.
sensor shaping error uncertainty
1.00
0.577
0.3333
6.
sensor temperature drift uncertainty
0.00
0.577
0.0000
7.
sensor noise uncertainty
0.95
0.500
0.2256
8.
sensor zero drift uncertainty
1.58
0.577
0.8311
9.
sensor calibration factor uncertainty
4.09
0.500
4.1820
___________________________
Total worst case uncertainty:
±18.43%
Total sum of squares:
29.936 %
2
Combined Standard uncertainty U
C
(RSS) :
±5.47 %
Expanded Uncertainty U (coverage factor k = 2) :
±10.94 %
From this example, it can be seen that the two largest contributions to total uncertainty are the source mismatch, and
the sensor calfactor. Also note that the expanded uncertainty is approximately one-half the value of the worst-case
uncertainty. This is not surprising, since the majority of the uncertainty comes from just two sources. If the measurement
frequency was lower, these two terms would be reduced, and the expanded uncertainty would probably be less than
half the worst-case. Conversely, if one term dominated (for example if a very low level measurement was being
performed, and the noise uncertainty was 30%), the expanded uncertainty value would be expected to approach the
worst-case value. The expanded uncertainty is 0.45dB.