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A methodology is being developed for classifying types of underlying surfaces based on radar frames (RF) of the flow in the forward viewing area of small-sized airborne radar stations of a multi-position system. Direct and inverse classification problems are solved to determine new reference models in order to construct maps of underlying surface zones based on statistical characteristics without the use of optical location visual information. To construct standards, it is necessary to solve the inverse problem, in which the initial data is the data from the combination of the optical and radar layers of the frame. The solution to the inverse problem depends on the quality of the result of solving the direct problem. When implementing the direct task, radar and optical images are combined. A radar flow is formed from reflected signals from the underlying surface based on a modification of the method of radar synthesis of the antenna aperture with a frequency comparable to the video frequency. The optical image can, for example, be a digital terrain map pre-loaded into the aircraft's memory, or an optical image recorded in an optical location system. As a result of this combination, a complex location image is formed, which is the input data for solving the inverse problem. The purpose of this research is to develop a methodology for classifying territories according to radar flow for constructing an appropriate (classification) map of the area based on segmentation methods, combining heterogeneous images, methods of remote sensing of the Earth, methods of mapping the earth's surface and searching for reference mathematical (statistical) models of echo signals, which are basis for classification of small-sized airborne radars in spatially distributed systems. The practical significance of these studies lies in the fact that a new methodology for classifying territories is proposed, implemented in the equipment of multi-position systems on small aircraft for solving problems of environmental monitoring, as well as assessing vegetation cover and land use, in particular forestry, agriculture, as well as coastal, aquatic and marshy areas. boundaries of divisions of various zones to unlock the potential of using territories.
Nenashev et al. (Mon,) studied this question.