Masters Theses

Jiangshuai Li

Keywords and Phrases

Emission sources; ESM; Gaussian regression; Location; Radiation power; Smart scanner

Abstract

“Emission source microscopy (ESM) technique can be utilized for localization of electromagnetic interference sources in complex and large systems. In this work a Gaussian process regression (GPR) method is applied in real-time to select sampling points for the sparse ESM imaging using a motorized scanner. The Gaussian process regression is used to estimate the complex amplitude of the scanned field and its uncertainty allowing to select the most relevant areas for scanning. Compared with the randomly selected samples the proposed method allows to reduce the number of samples needed to achieve a certain dynamic range of the image, reducing the overall scanning time. Results for simulated and measured 1D scans are presented.

This method allowed to reduce the number of samples needed to achieve a certain dynamic range of the image, reducing the overall scanning time and eliminating a need of human intervention into the ESM process. Based on the work of 1D scan and Gaussian Regression Sparse ESM strategy, the second work in this paper extends the application of the ESM with GPR sampling to 2D scenes with multiple sources, including distributed ones.

The automatic GPR ESM method can intelligently and automatically control the scanning process, reducing the number of measurement points with less image quality degradation compared to the random ESM scanning”--Abstract, page iv.

Advisor(s)

Beetner, Daryl G.

Committee Member(s)

Khilkevich, Victor
Kim, DongHyun

Department(s)

Electrical and Computer Engineering

Degree Name

M.S. in Electrical Engineering

Research Center/Lab(s)

Electromagnetic Compatibility (EMC) Laboratory

Publisher

Missouri University of Science and Technology

Publication Date

Spring 2022

Journal article titles appearing in thesis/dissertation

  • Automatic sparse ESM scan using Gaussian process regression
  • Measurement of the total radiated power contributions in a reverberation tent

Pagination

x, 41 pages

Note about bibliography

Includes bibliographic references.

Rights

© 2022 Jiangshuai Li, All rights reserved.

Document Type

Thesis - Open Access

File Type

text

Language

English

Thesis Number

T 12119

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