Our analysis and measurements of a custom-designed two-port microstrip test fixture for biological tissue characterization at microwave and millimeter-wave frequencies demonstrated that the transmission parameter S21 would provide a better sensitivity to the complex permittivity change than the reflection coefficient S11. However, the standard through-reflect-line (TRL) calibration method employed for the extraction of the tissue complex permittivity did not fully remove the coaxial-to-microstrip adaptors' induced errors, which were manifested by ripple artifacts on the measured two-port S parameters. A simple deconvolution method was demonstrated wherein these errors were removed by postcalibration correction of the measured S21 of the tissue under test (TUT) by using water as a reference material. This paper provides a theoretical analysis of this method based on a model presented for postcalibration adaptors. Our detailed analysis shows that the error for S21 using the deconvolution method linearly depends on the difference between the S11 of the TUT and the reference material. Measurement and error estimation are also provided for various biological tissues and are consistent with analytical expectations. Our analysis provides support that systematic errors of numerically modeled S21 utilized for complex permittivity extraction can significantly be reduced by the deconvolution method. On the other hand, the analysis also shows that the S21 numerical modeling errors and the postcalibration adaptors' error terms have a similar impact on the extracted complex permittivity using the standard time-gating technique and are irreducible, unless the deconvolution method is used. Our analysis also identifies water as a better reference sample than methanol for accurate extraction of the complex permittivity of tissues in the range of ε′ > 9 and ε″ > 7 at 30 GHz.
|Original language||English (US)|
|Number of pages||12|
|Journal||IEEE Transactions on Instrumentation and Measurement|
|State||Published - Feb 26 2009|
All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering