Development of the method for increasing the accuracy of localization of wireless sensor networks - Pastushenko, Hanna (INNOVATIVE TECHNOLOGIES AND SCIENTIFIC SOLUTIONS FOR INDUSTRIES, 2025)
The subject of the study in the article is methods for increasing the localization accuracy in wireless sensor networks in open environments. Particular attention is paid to methods for adjusting the signal transmission power to determine the communication ranges between reference and unknown nodes, as well as methods for optimizing localization through multi-step narrowing of the search area of possible node locations. The purpose of the work is to develop an effective method that increases the localization accuracy of wireless sensor network nodes by adjusting the signal transmission power to gradually narrow the search area, using multi-round measurement to improve localization results, and statistical analysis to predict the location of nodes. The following tasks are solved in the article: 1) development of a method for adaptively adjusting the signal power; 2) development of an algorithm for multi-round narrowing the search area; 3) use of statistical methods for predicting node positions. Methods used in the study: adaptive signal power adjustment method; algorithm for multi-round narrowing the search area; statistical analysis for predicting the location of a node. Results. A method is proposed that allows to significantly increase the localization accuracy in wireless sensor networks. As a result of experiments, it was shown that, compared to traditional methods, the new approach reduces positioning errors by 30–40%, which is a significant achievement for networks operating in open environments. In some cases, the method allows to accurately determine the location of a node already at a late stage of measurements. This allows to reduce energy consumption, since the number of necessary measurements and checks is significantly reduced. The developed approach demonstrates its effectiveness even in cases where signals are subject to significant interference, thanks to adaptive adjustment of the signal transmission power. Conclusions. The use of the method increases the localization accuracy in wireless sensor networks, which is important for IoT applications. This reduces energy consumption due to the lower need for measurements. Further research may focus on adaptation to more complex conditions, such as urban environments or indoor spaces.