Page 365 - Microsensors, MEMS and Smart Devices - Gardner Varadhan and Awadelkarim

REFERENCES 345

A series of known standards are connected to the system during calibration. The
systemic effects are determined as the difference between the measurand and the known
response of the standards. These errors can be mathematically related by solving the
signal-flow graph (Subramanian 1998). The frequency response is the vector sum of all
test setup variations in magnitude and phase and the frequency. This is inclusive of all
signal-separation devices, such as test setup and cabling.
The mathematical process of removing errors is called error correction. Ideally, using
perfectly known standards, these errors should be completely characterised. The measure-
ment system is calibrated using the full two-port calibration method. The four standards
that are commonly used are shielded open circuit, short circuit, load, and through. This
method provides full correction of directivity, source match, reflection and transmission-
signal path, frequency response, load match, and isolation for S 11, S 12, S 21, and S 22. The
procedure involves taking a reflection, transmission, and isolation measurement.
For the reflection measurement (S 1 1 , S 22 ), the open, short, and load standards are
connected to each port in turn and the frequency response is measured. These six measure-
ments result in the calculation of the reflection error coefficients for both ports.
For the transmission measurement, the two ports are connected and the following
measurements are carried out forward through transmission (S21 -frequency response),
forward through match (S21-load), reverse through transmission (S 12-frequency response),
and reverse through match (S 12-load). The transmission error coefficients are computed
from these four measurements.
Loads are connected to the two ports and the S 12 and S 21 noise floor level is
measured. From these measurements, the forward and reverse-isolation error coefficients
are computed. The calibration is saved in the memory of the network analyser and the
correction is turned on to correct systemic errors that may occur.
By making these measurements, it is possible to identify the critical acoustic parameters
and thus design the optimal IDT-SAW microsensor. The SAW microsensor may now be
fabricated, and the process is provided in the following chapter.

REFERENCES

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MS thesis, Pennsylvania State University, USA.
Grate, J. W., Martin, S. J. and White, R. M. (1993). "Acoustic wave microsensors, Parts I and II,"
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HP 8510B Network Analyzer Manual (1987). Hewlett-Packard Company, Santa Rosa, Calif.
Piscotty, D. J. (1998). 150 MHz wireless detection of a ST-cut quartz substrate surface acoustic
wave device, MS thesis, Pennsylvania State University, USA.
Shiokawa, S. and Moriizumi, T. (1988). Design of SAW sensor in liquid, Proc. of 8th Symp. on
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