METHODS OF MEASURING DISTANCES BETWEEN OBJECTS IN SENSOR NETWORKS USING DIGITAL FREQUENCY MEAN VALUES

Relevance of the research topic. At the moment, wireless sensor networks are an important tool for exploring the physical world. Their importance is related to new uses, thanks to such characteristics as the lack of the need for cable infrastructure, miniature nodes, low power consumption, built-in radio interface, sufficiently high transmission power, relatively low cost. Therefore, there is a problem of creating new tools that would improve the effectiveness of their use, which would give an opportunity to expand the scope of their application. Formulation of the problem. In the process of developing such systems, developers have to solve the contradiction between the decrease in the accuracy of the distance measurement, the increasing range of the objects, the limited power of the transmitters, and the cost of special nodes that receive the exact coordinates from the satellite. The presence of these restrictions increases the probability of errors when localizing objects in wireless sensor networks. Analysis of recent research and publications. The latest publications were publicly available, including existing distance measurement algorithms and energy efficiency problems for transmitters. Isolation of previously unexplored parts of a common problem. Increase the accuracy of measuring the distance of means using existing distance measurement algorithms. Formulation of the problem. Improving the method of distance measurement by devices of wireless sensor networks, by using microprocessor frequency meters. Statement of the main material Localization of objects occurs using the TDOA (Time Difference of Arrival) method. The data obtained after using this method is sent to the microprocessor frequency meter, which determines the period between the phases of the signal, proportional to the value to the distance between objects. Conclusions in accordance with the article The proposed method makes it possible to improve the accuracy of the process of localizing objects in wireless sensor networks.