Аннотация
Application of GPR in restoring the structure of the underground environment can be reduced to the solution of ill-posed problems for hyperbolic and parabolic types of equations. Many researchers describe algorithms for this kind of problems. At present, methods of interpretation georadarograms can be improved by new achievement of the inverse problems theory. The bottleneck of application of GPR is the complexity of interpreting data required at the present stage to attract highly qualified professionals. Forming of own methods of interpreting GPR data contributes to preservation of confidential geophysical information. The main area of application of the wavelet transforms is the analysis and processing of signals and functions that are nonstationary in time or inhomogeneous in space, when the results of the analysis should contain not only the frequency response of the signal (signal energy distribution by frequency components), but also information about local coordinates, on which some groups of frequency components are expressed or on which rapid changes in the frequency components of the signal take place [1]. In comparison with the decomposition of signals into Fourier series, wavelets can represent local features of signals with much higher accuracy. A discrete wavelet transform can be used to easily and quickly remove noise from a noisy signal. If we leave only a limited number of the highest coefficients of the spectrum of the discrete wavelet transform, and carry out the inverse wavelet transform, we can get a signal cleared of noise. A copper cable buried at a depth of 122 cm will be used as a research object. The result of the georadar survey is a set of single tracks (signals), registered by the receiving antenna at each position of the radar. The radar scan of the cable scan was obtained by the GPR `LOZA' (Figure 1). The trace of this radargram is processed by the Wavelet Toolbox, and by the System of numerical and mathematical modeling MatLab [2].