Modeling the Detection of Moving Objects by Means of a Spatially Distributed Continuous Monitoring System with a Dynamic Structure
Main Article Content
The class of monitoring systems, which is equipped with mobile means of detection, is considered. Unmanned aerial vehicles are used as detection means. The area of responsibility of the system is a geographic space with counteraction for both detection equipment and objects of observation. An original approach to the development of a simulation model for detecting moving objects of observation in the area of a spatially distributed continuous monitoring system with a structure is proposed. The movement of sensors is displayed along trajectories, which are Hamiltonian cycles on the terrain graph. The new approach is to use the approach used to ensure the flexibility of the resulting solutions to the problem of monitoring space and the ability to respond quickly to various factors and other conditions of use based on self-organizing mechanisms. At the same time, both the system itself, designed to solve the tasks of continuous monitoring and the solutions found for specific monitoring tasks and spatially distributed systems, provide continuous monitoring and are resistant to destructive influences of various kinds.
The constructed simulation model and the experiments performed using the principles of dynamic detection of detection means in the area of a spatially distributed continuous monitoring system. At each moment of time, the optimal configuration of the parameters is determined, which is used as the most effective solution of the problem from the point of time of detecting an object in the monitoring area of vision. The model does not depend on the type of sensors used in the network and the implementation of the ideological principles embodied in the concept of dynamic systems. Based on the results of the experiments carried out, conclusions are drawn about the characteristics of continuous monitoring, which provides a basis for further work to optimize these indicators.