Statistical Data Processing of Two Mobile Objects Behavior in Random Environments Using Simulation Modeling Method

摘要

The article substantiates the necessity of using simulation in order to study the behavior of mobile aircraft (MA) in non-deterministic random environments. The purpose of research using a simulation model is to obtain statistical data on the behavior of the MA with antagonistic tasks. The processing of statistical data allows concluding which one of the MA and with which characteristics solves the problem more successfully. An analytical review of papers in this research area is carried out. The results of the analytical review have indicated the relevance of these studies. Methods for solving the problem of studying the MA behavior are probability theory and mathematical statistics, as well as simulation. It is shown that a non-deterministic random environment has many random parameters. A simulation model for studying the MA behavior is developed. Algorithms of the MA behavior are developed for the simulation model. It implemented in Unity3d - a software environment for modeling various processes. For simulation, an object-oriented C # high-level programming language is used. In order to solve the problem of studying the MA behavior, a list of estimates (criteria of behavior) from probability theory and mathematical statistics is defined. The use of a simulation model allows getting many statistical data and processing them in order to determine estimates. A description of the source data and the operation of the software application for solving the problem of modeling the interaction of two mobile objects is given. In the study of behavior, the first and second MA are assigned different tasks. This has determined the MA different goals and the algorithms for their behavior. Algorithms for the simulation of the MA behavior are developed and tests are carried out using a software application. As a result of simulation, statistical data is obtained and processed. The use of a simulation model and the method of its development allows solving the problem for any MA number. Simulation allows predicting the achievement of the MA goal, and with a more complex statement of the problem, selecting the MA number in order to solve the problem.