Efficient Determination of Reverberation Chamber Time Constant

被引:10
|
作者
Zhang, Xiaotian [1 ]
Robinson, Martin P. [1 ]
Flintoft, Ian D. [2 ]
Dawson, John F. [1 ]
机构
[1] Univ York, Dept Elect Engn, York YO10 5DD, N Yorkshire, England
[2] Elect Syst Practice, York YO1 6HZ, N Yorkshire, England
关键词
Absorption cross section (ACS); chamber time constant; inverse Fourier transform; Monte Carlo method; power balance method; power delay profile (PDP); reverberation chamber (RC); ABSORPTION CROSS-SECTION; COMPLEX PERMITTIVITY; PARAMETERS; BANDWIDTH; OBJECTS; MODEL;
D O I
10.1109/TEMC.2017.2776559
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Determination of the rate of energy loss in a reverberation chamber is fundamental to many different measurements such as absorption cross section, antenna efficiency, radiated power, and shielding effectiveness. Determination of the energy decay time constant in the time domain by linear fitting the power delay profile, rather than using the frequency-domain quality-factor, has the advantage of being independent of the radiation efficiency of antennas used in the measurement. However, determination of chamber time constant by linear regression suffers from several practical problems, including a requirement for long measurement times. Here, we present a new nonlinear curve fitting technique that can extract the time constant with typically 60% fewer samples of the chamber transfer function for the same measurement uncertainty, which enables faster measurement of chamber time constant by sampling fewer chamber transfer function, and allows for more robust automated data postprocessing. Nonlinear curve fitting could have economic benefits for test houses, and also enables accurate broadband measurements on humans in about 10 min for microwave exposure and medical applications. The accuracy of the nonlinear method is demonstrated by measuring the absorption cross section of several test objects of known properties. The measurement uncertainty of the method is verified using Monte Carlo methods.
引用
收藏
页码:1296 / 1303
页数:8
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