Author:
Makhov V.E.,Sytko I.I.,Shirobokov V.V.
Abstract
Optical observation is the most effective way to control the state of various objects. The dynamism of the objects of the observed scene makes it an urgent task to improve the algorithms for obtaining coordinate and non-coordinate information about the observed objects. The issues of increasing the accuracy of measuring the distance and increasing the resolution between the light objects observed by the optical system by the method of double continuous wavelet transformation are considered. It is shown that the use of the second continuous wavelet transform to the curves of the coefficients of the first transform leads to an increase in the maxima of the scalegram and the curves of the coefficients, providing the coordinate sensitivity of the position of the signals by more than two times. The use of different types of wavelets in each continuous wavelet transform of signals gives many options for constructing a processing algorithm and can be used for additional filtering of noise taking into account the characteristics of signals. In this regard, it is proposed to use parallel mathematical models and real signals in a neural network for determining the coordinates of signals and their characteristics, which leads to an increase in accuracy for each type of signal. The indicated approach can be used in systems for multiple signaling from different sources or for combining images in multi-position systems.