Sparse Emission Source Microscopy for Rapid Emission Source Imaging
Emission source microscopy (ESM) technique can be utilized for the localization of electromagnetic interference sources in complex and large systems. This paper presents a sparse and nonuniform sampling technique for ESM. Compared with the traditional way of acquiring abundant and uniformly distributed scanning points on the scanning plane using a robotic scanning system, the proposed method is much more time-efficient in identifying the major radiation sources, even though the image quality is sacrificed. The feasibility of sparse sampling is mathematically proved, and it is shown that increasing number of scanning points increases the signal-to-noise ratio of reconstructed images. Besides, a nearest neighbor interpolation method is applied in the real-time processing to estimate the radiated power through the scanning plane. Thus, back-propagated images and estimated radiated power can be obtained in the real-time measurement process, which can efficiently and instantaneously provide the locations and the radiation strength of the most significant emission sources.
L. Zhang et al., "Sparse Emission Source Microscopy for Rapid Emission Source Imaging," IEEE Transactions on Electromagnetic Compatibility, vol. 59, no. 2, pp. 729-738, Institute of Electrical and Electronics Engineers (IEEE), Apr 2017.
The definitive version is available at https://doi.org/10.1109/TEMC.2016.2639526
Electrical and Computer Engineering
Electromagnetic Compatibility (EMC) Laboratory
Keywords and Phrases
Electromagnetic pulse; Scanning; Signal to noise ratio; Emission sources; Nearest neighbor interpolation; Nonuniform sampling; Radiation source; Real time measurements; Realtime processing; Reconstructed image; Scanning systems; Image processing; Emission source microscopy (ESM); radiated power; source localization; sparse sampling
International Standard Serial Number (ISSN)
Article - Journal
© 2017 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
01 Apr 2017