Evaluation Method of Uncertainty in Noise Parameter Measurement Based on Monte Carlo Method
A technology for measuring uncertainty and noise parameters, applied in special data processing applications, electrical digital data processing, instruments, etc., can solve the difficulty of uncertainty application, no inclusion factor is given, and there is no uncertainty in the measurement results of packaged device fixtures Degree and other issues
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Publication Date
- 2015-09-16
Smart Images
Figure 1 Figure 2 Figure 3
Abstract
Description
technical field
[0001] The invention discloses a noise parameter measurement uncertainty evaluation method based on a Monte Carlo method, which belongs to the field of test and measurement. Background technique
[0002] "Guide to the Expression of Uncertainty in Measurement" (Guide to the Expression of Uncertainty in Measurement, referred to as GUM) has been published in 1993, and after years of promotion and application, it has become a uniform standard followed by all countries when expressing measurement results. In China, the measurement technical specification JJF1059-1999 "Evaluation and Expression of Measurement Uncertainty" is equivalent to the method stipulated by GUM. It has played an important role in guiding and regulating the use and evaluation of measurement uncertainty throughout the country. , The expression of measurement results in the test field is in line with international standards.
[0003] With the rapid development of science and technology and the ...
Examples
Embodiment Construction
[0047] Depend on figure 1 and figure 2 The present invention is shown and described in detail with reference to specific embodiments.
[0048] The measurement uncertainty evaluation method of noise parameters based on the Monte Carlo method is used to evaluate the measurement uncertainty of the noise parameters of the device under test in this embodiment.
[0049] The first step is to build a noise parameter measurement platform.
[0050] Such as figure 1 As shown, the measurement platform includes a noise source, a vector network analyzer, a noise figure analyzer, an impedance adjuster, an input DC bias network, an output DC bias network, and a DUT; the output of the noise source is sequentially The input end DC bias network, the impedance adjuster, the DUT and the output end DC bias network are connected to the corresponding input ends of the noise figure analyzer; the vector network analyzer is set between the noise source and the noise figure analyzer Between, set in ...