The article presents an information technology for determining monitoring areas when planning an unmanned aerial vehicle flight in order to find a dynamic object. The job of site identification information technology is to screen out low-weight sites based on the UAV's current location and time of arrival at the site. To determine the priority monitoring point, the averaged value of the section weight was applied, which takes into account the section weight proportional to the monitoring time and the expediency of the flight to it. The information technology for site determination is based on a combination of greedy, sorting and brute-force algorithms.The developed information technology can be included in the scientific and methodological apparatus and flight planning tools for an unmanned aerial vehicle, including a group, when performing a mission to find a dynamic object. For the experiment, a program for planning an unmanned aerial vehicle was developed on the Embarcadero Builder XE8 platform in the C++ programming language. An experiment was carried out as a result of which the flight route of an unmanned aerial vehicle was obtained. The information technology developed in the article for determining the monitoring sites will reduce the time when planning missions and increase the efficiency of air reconnaissance in general.

The subject matter of the article is the process of developing information technology for the automated detection and identification of stationary objects by unmanned aerial vehicles arises. The goal of the study is to development of the main points for information technology of automated detection and identification of stationary objects by unmanned aerial vehicles. The tasks to be solved are: the structural diagram of the preparatory stage of information technology for automated detection and identification of stationary objects is constructed; the structural diagram of the basic, additional and final stages of information technology automated detection and identification of fixed objects is constructed. General scientific and special methods of scientific knowledge are used. One of the most effective approaches to the recognition and identification of objects is an approach based on the use of deep learning methods. A new model of UAV motion is proposed based on image recognition methods. The methods of pattern recognition with application of neural networks are considered in detail in this work too. The following results are obtained. The developed information technology is implemented in four stages: preparatory, basic, additional and final. Each stage consists of separate procedures aimed at collecting, processing, storing and transmitting information during the flight UAV. Conclusions. Information technology for the automated detection and identification of stationary objects by unmanned aerial vehicles is based on the knowledge-oriented representation of the stages of image processing of objects on digital aerial photographs on board the UAV. This allows to provide intelligent real-time data processing, changing UAV flight routes depending on the objects detected to improve the effectiveness of the search tasks. Further development of this information technology lies in the development of automated methods of planning UAV routes, automatic change of route parameters in flight processes (performance of a flight task), based on knowledge-oriented technologies. Information technology for the automated detection and identification of stationary objects by unmanned aerial vehicles can become an element of intelligent decision support systems for the use of UAVs (teams of UAVs) to search for both stationary and dynamic objects.

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A further development of the method of calculating the errors for the coordinates of the binding objects and the angle parameters of the orientation of unmanned aerial vehicles is obtained. Errors of determination of coordinates develop due to the impact of wind gust and turbulence of the atmosphere on light unmanned aerial vehicles. The main feature of the method is the ability to determine the error of the coordinates of the objects, depending on the direction and force of influence on the unmanned aerial vehicle. The magnitude of the external influence determines the value of the deviation from the trajectory of motion. The developed method can be applied with limited mass-size characteristics of an unmanned aircraft. It also determines the values of measurement errors regardless the distance between the points of measurement. Limitation to the application of the method can only be the ability of the appropriate sensors to measure the distance from the unmanned aircraft to the object of anchor. Possibilities of determining the coordinates of an object of binding with accuracy within units of measure are presented. This is achieved by measuring the angular coordinates with sensors of the navigation system accurately within a hundred miliradian. An algorithm for calculating the error of determining the coordinates of the binding object is presented. The algorithm is the further development of the sub-algorithm for calculating the angle parameters of the orientation of an unmanned aerial vehicle relative to the geographical coordinate system. The presented algorithm should be used before the start of the session of the correlation-extreme navigation system. The statistical simulation of the proposed method and algorithm is carried out. The results of the simulation indicate that the magnitude of the error of determining the coordinates of the binding object depends on the accuracy of the measurement of the angular parameters of an unmanned aerial vehicle. The results of the numerical estimation of the errors of measurement of coordinates of the binding objects are presented, depending on the accuracy of the measurement of the angular parameters of the unmanned aerial vehicle. The requirements for the accuracy of measuring the angular parameters of an unmanned aerial vehicle are determined, which provides a high accuracy of measuring the rectangular coordinates of the object of anchor. K e ywor d s : platform free inertial navigation systems, binding object, system of rectangular coordinates, angle of vision.