Rational analyzing function for precise feature extraction from an electrostatic signal

DOI: 10.34759/trd-2021-119-14

Аuthors

Scriabin Y. M.^*, Potechin D. S.^**

MIREA — Russian Technological University (Lomonosov Institute of Fine Chemical Technologies), 78, Vernadsky prospect, Moscow, 119454, Russia

*e-mail: meh-record@yandex.ru
**e-mail: msyst@msyst.ru

Abstract

The article is devoted to the problem of extracting features from an electrostatic signal. This problem becomes relevant when using an electrostatic monitoring system to detect unmanned aerial vehicles. The law of variation of the electrostatic field tenseness at a particular point on the earth’s surface depends on the landscape. In addition, the process of determining the parameters of the UAV flight requires the precise of determining the signs of an electrostatic signal.

In the works of other researchers, the wavelet transform based on the Morlet function is usually used to extract the features of an electrostatic signal. The exact definition of the features is carried out from the analysis of the resulting three-dimensional time-frequency distribution.

In this paper, we consider another type of transformation of an electrostatic signal based on convolution with a complex rational function. We select a function that can provide a simpler time-frequency distribution. The simplicity of this distribution lies in the fact that the parameters of the electrostatic signal are extracted based on determining the intersection point of two two-dimensional functions, instead of determining the peak on the three-dimensional distribution in the case of the wavelet transform.

The method under consideration has comparable noise immunity compared to the wavelet transform, in addition, it allows you to adapt the transformation to a specific electrostatic signal.

Keywords:

UAVs detection, electrostatic monitoring technology, electrostatic signal, time-frequency representations

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