Investigation on probability distribution models of electric field in reverberation chamber

被引:0
|
作者
Tan, Wuduan [1 ]
Yu, Zhiyong [1 ]
Song, Jianshe [1 ]
机构
[1] The Second Artillery Engineering University, Xi'an 710025, China
来源
关键词
Bivariate - Cartesian components - Cartesians - Classical probabilities - Field components - Gaussian distribution model - Goodness-of-fit test - Imaginary parts - Marginal distribution - Marginal probability - Probability density function (pdf) - Probability distribution model - Rayleigh - Rejection rates - Reverberation chambers - Statistical distribution - Statistical models - Uniform distribution - Weibull - Working volume;
D O I
10.3969/j.issn.1003-6520.2012.09.030
中图分类号
学科分类号
摘要
Because of higher rejection rates in goodness-of-fit tests, the classical probability distribution model of electric field in reverberation chamber (RC) cannot exactly describe the statistical distribution law of electric field in actual RC. So a novel statistical model of the electric field is derived based on the study of the statistical distribution law of the electric field in RC.On the basis of the assumption that both the real and imaginary parts of each Cartesian field component within the working volume of RC follow a Gauss-normal probability density function (PDF), a complete bivariate joint Gaussian distribution function is induced to describe two variables contained probability distribution model, which is formed by the real and imaginary parts of each Cartesian field component. Novel theoretical probability distribution models for the magnitude and phase of electric field Cartesian component inside RC are derived by means of marginal PDFs integrated with the joint Gaussian distribution model. The marginal probability distribution models have smaller rejection rates than Rayleigh, Weibull and uniform distribution in goodness-of-fit tests in an actual RC. The results prove that marginal probability distribution models are able to describe the statistical distribution of the electric field in RC more precisely.
引用
收藏
页码:2349 / 2353
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