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

Abstract

In this paper, one of the subspace signal processing methods, namely time reversal multiple signal classiflcation (TR- MUSIC), is flrstly 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 deflned 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.