Geophysical research: article

Peculiarities of correlation processing of pseudonoise signals in electrical prospecting equipment
V.V. Bobrovsky
Research Station of the Russian Academy of Sciences, Bishkek, Kyrgyz Republic
Journal: Geophysical research
Tome: 23
Number: 2
Year: 2022
Pages: 39-54
UDK: 550.380.83 / 004.42 / 004.021
DOI: 10.21455/gr2022.2-3
Full text
Keywords: geoelectrical exploration, pseudonoise signals, correlation processing of signals, structural disturbances
Аnnotation: The paper presents an algorithm for eliminating structural disturbances arising on the transient response curve in the process of correlation processing of the registered pseudonoise signals. The algorithm is based on the detection and selection of impulse signals of structural disturbances against the background of smoothly (slowly) varying transient. The energy of detected impulse signals of structural disturbances exceeds the optimal detection threshold calculated from the transient response curve. This method provided reliable, with a high probability of correct detection and a low probability of a false alarm, detection and further elimination on the resulting transient response curve of structural disturbances. A criterion for automatic calculation of the optimal threshold for detecting structural disturbances is proposed, based on the maximum approximation to the normal distribution law of the disturbances and noises remaining on the transient response curve after removing structural disturbances from it. The choice and determination of the optimal detection threshold is carried out in the process of sequential enumeration of its values (from maximum to minimum) with a set step that determines the accuracy of determining the threshold. The procedure for finding the detection threshold is reduced to finding the maximum value of the Pearson correlation coefficient calculated at each step between the probability density distribution functions and the calculated normal distribution law of the amplitudes of noises and disturbances remaining on the transient response curve after removing the structural disturbances. This made it possible to automate the data processing process to the maximum and increase its speed, which is very important when performing work in the field. The algorithm was worked out on transient signals, obtained at the experimental point “Chunkurchak”, during the field work with an electrical prospecting measuring complex with pseudonoise signals. The application of the algorithm made it possible to significantly (approximately by 450 times) improve the signal-to-noise ratio on the transient response curve in the region of large times.
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