UWB Subsurface Radiolocation for Object Location Classification by Artificial Neural Networks Based on Discrete Tomography Approach

Abstract

The two-dimensional problem of the subsurface object depth determination is solved by the impulse electromagnetic plane wave irradiation of the surface and analysis of reflected wave received by set of probes placed above the surface. The analysis of the signals is carried out by means of artificial neural networks (ANN) improved by additional data usage from the signals and parameters of structure. The problem of Gaussian pulse propagation in the subsurface medium with objects is solved by FDTD method. The electrical field strength amplitudes above the model of a ground in a number of time points form a first part of the set of input data for a multilayer ANN. The second part of input data includes a special linear superposition of data from the first part with coefficients received on the base of discrete tomography approach and ray tracing method. The work of the ANN is verified by the problem of impulse electromagnetic wave irradiation of perfectly conducting object inside ground. The precision of the determination of the object depth and influence of the second part of input data are investigated for test cases.