Boonton 4500B Peak Power Meter - Manual (Page 329)

Boonton 4500B RF Peak Power Analyzer
Application Notes 6-19
Sensor Temperature Coefficient. This term is the error which occurs when the sensor‘s temperature has changed
significantly from the temperature at which the sensor was AutoCal‘d. This condition is detected by the Model
4500B and a ―temperature drift‖ message warns the operator to recalibrate the sensor for drift exceeding ±4C on
non-temperature compensated peak sensors. For these sensors, the typical temperature effect 4 degrees from the
AutoCal temperature is shown as a graph versus level on the sensor datasheet.
Temperature compensated peak sensors have a much smaller temperature coefficient, and a much larger temperature
deviation, ±30C is permitted before a warning is issued. For these sensors, the maximum uncertainty due to
temperature drift from the autocal temperature is:
Temperature Error = ± 0.04dB (0.93%) + 0.003dB (0.069%) /degreeC
Note that the first term of this equation is constant, while the second term (0.069%) must be multiplied by the
number of degrees that the sensor temperature has drifted from the AutoCal temperature.
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 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) × 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) × 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.