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Progress In Electromagnetics Research
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ELECTROMAGNETIC SUBSURFACE DETECTION USING SUBSPACE SIGNAL PROCESSING AND HALF-SPACE DYADIC GREEN'S FUNCTION

By X.-F. Liu, B.-Z. Wang, and S.-Q. Xiao

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Abstract:
In this paper, one of the subspace signal processing methods, namely time reversal multiple signal classification (TR-MUSIC), is firstly employed for electromagnetic subsurface detection where the multilayered dyadic Green's function is used. Therewith, one obtains the improved location and superresolution imaging for underground detecting application. The imaging pseudo-spectrum is accordingly defined for both the echo-mode and transmit-mode TR-MUSIC methods, by analyzing the obtained multistatic response matrix. Based on the theoretical formula, we carry out the numerical simulation using the half-space dyadic Green's function in noisy scenario. The results show that the MUSIC imaging algorithm achieves the enhanced resolution and the transmit-mode method gives more robust output when performance comparison of the four methods is made, therefore indicate the TR-MUSIC could be a good candidate for subsurface detection.

Citation:
X.-F. Liu, B.-Z. Wang, and S.-Q. Xiao, "Electromagnetic Subsurface Detection Using Subspace Signal Processing and Half-Space Dyadic Green's Function," Progress In Electromagnetics Research, Vol. 98, 315-331, 2009.
doi:10.2528/PIER09092902
http://www.jpier.org/PIER/pier.php?paper=09092902

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