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Analysis of the Effect on Image Quality of Different Scanning Point Selection Methods in Sparse ESM

Sparse emission source microscopy (ESM) is an efficient method to identity radiating sources. With the purpose to minimize the number of required measurement points, the presented work investigates how numerical properties of sparse ESM affects the quality of source reconstruction. A simulation model of a simple printed circuit board was used instead of measurements to isolate the observed effect of the two-dimensional (2-D) discrete Fourier transformation (DFT) and the plane wave spectrum's numerical properties. The paper shows that sub-Nyquist is achievable and suggests uniform sampling is superior to nonuniform, in contrast to other reported uses of microwave imaging. Finally, the study shows that if the source reconstruction is based on uniform 2-D DFT care should be taken with the previously suggested intelligent selection of sparse samples based on real-time observation of the measured field.