The military aggression carried out by the russian federation against Ukraine for more than eight years has significantly increased the volume of military development by the military-industrial complex of Ukraine. Considering the special importance and danger of the developed samples of weapons and military equipment, the issue of their high-quality and timely testing is crucial. The flow of samples of weapons and military equipment, which are sent to the testing organization for research, may have heterogeneity in the importance of samples for immediate mass production and supply to the troops. The priority that arises in the flow of tested samples can negatively affect the timeliness of testing non-priority samples and the throughput of the testing organization as a whole, which,in turn, forces the search for methods of effective organizational management of the testing process.The article deals with the development of a test system model. To model and analyze the processes that affect the performance of the testing organization, a multi-phase system of mass service is used, in which the main stages of the test are represented by phases. Determined with the help of statistical analysis of the incoming flow of samples arriving for testing and the processes of servicing these samples, it was possible to model the main stages of the test according to the scheme of Markov processes. The model introduces the concept of the average number of the test team, which makes it possible to analyze the effectiveness of the distribution of personnel, which in the conditions of mass tests is a limited resource of the organization. For various stages of testing, the conditions for the receipt of priority samples, the features of maintenance of priority samples and their impact on the performance ofthe testing system are formalized. The main analytical ratios that determine the successful functioning of the test system are derived.It is assumed that the implementation of the model is possible as part of an automated test support information system for analyzing the performance of the test process and developing organizational solutions aimed at optimizing the functioning modes

A scheme of interrelationships of external and internal macro- and microenvironmental factors and their influence on the states of the unmanned aerial vehicle system has been developed. It is proposed to use an approach with elements of graph theory and set theory to analyze the states of an unmanned aircraft complex. The given graph of the functioning of the man-machine system of a sample of the unmanned aircraft complex of the “micro UAS unmanned aircraft system” class sets the transitions that determine the closed cycle of the execution of a combat mission. An example of building a structure of functional indicators of unmanned aerial vehicles with life cycle elements using graph theory for the analysis of “bottlenecks” in ensuring reliability is given. The analysis of “bottlenecks” in the control systems of unmanned aerial vehicles in the area of the ground control station – unmanned aerial vehicle is aimed at determining directions for increasing reliability, flight safety, increasing functionality, flight range and improving ergonomic characteristics. A comprehensive analysis of the functioning and dynamics of changes in reliability indicators with relevant data for previous periods of operation will allow us to draw specific conclusions about the actual level of reliability of the UAS un manned aircraft system fleet and identify bottlenecks for further improvement and the possibility of transitioning to the use of third-generation BpAK (autonomous devices) with self-learning systems with artificial intelligence. The theoretical rationale and the given practical recommendations should be taken into account when developing new prospective models of unmanned aerial vehicles for the Armed Forces of Ukraine in accordance with their official purpose.

The article analyzes the approaches to the creation of mathematical models focused on determining the failure-free factors of unmanned aerial systems during their operation. It is noted that many economic and social processes can be narrowed down to the problem of the choice made by their participants between several alternative (mutually exclusive or competing) options. Examples include the problem of consumer behavior in a competitive market in which the consumer makes investment decisions in the context of choosing between several alternative projects; selection of possible transport systems for passenger and сargo transportation; choosing among alternative opportunities for the economic growth of territories, decision-making in speculative financial markets (using instruments to buy for a rise or sell short) and others. To ensure the possibility of determining the predicted failure-free factors at the stage of performance evaluation by methods of functional and structural analysis, a mathematical model of the process of determining failure-free factors was developed, focused on the use of dynamic Bayesian belief networks. The proposed model takes into account the Markovian character of the operation process running, in which failures of elements and subsystems are compensated by actions to restore the system. The failure rates of UAS during performance evaluation, as well as the average integral value survival rate for the period of performance evaluation, the rate of occurrence of failures and time to failure are determined as the final failure-free factors. The model is evaluated as a necessary condition for further development of specially configured software to solve the problem of determining failure-free factors of unmanned aerial systems.

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The calculation and accurate determination of the main indicator of radar visibility - radar cross-section is a complex problem for which theoretical and experimental methods have been developed. Theoretical methods for determining the radar cross-section at this time are quite accurate, but the priority area of research is still to determine the radar cross-section by the experimental method. One of such practical methods for determining the radar cross-section is a model (and for small unmanned aerial vehicles - full-scale) experiment in a anechoic screened chamber, but this experiment does not take into account the propagation properties of radio wave in real conditions. The most reliable characteristics of the unmanned aerial vehicle (UAV) radar visibility are obtained in a full- scale experiment during a testing ground experiment by test flight. Determination of the radar cross-section by the test flight method is carried out in real conditions under the influence of all available factors for the radio detection and location, methods of its processing, the presence of spurious reflection, the real jamming environment. A signals training area is used as a test range. A signals training area is an spatial region (sector of the terrain) where the instrumentation radar set and certain spatio measuring points arе located and the signal-noise-rate of the radar sеt receive path is measured when the unmanned aerial vehicle to be in the spatio measuring points. It should be noted that any radar set can be used as a instrumentation radar set, subject to conformity with the measurement accuracy meets the specified requirements. Given the above, the UAV radar visibility evaluation procedure during testing ground experiment by test flight allows to determine the radar cross-section in the absence of a perfect measuring system and provides a high level of measurement accuracy.