Minimizing Localization error in Wireless sensor networks Taguchi method

Localization is a key research area in wireless sensor networks. The study focuses on the system's behavioral analysis in terms of minimizing localization error by adjusting parameters such as nodes, network size, communication range, and network deployment. Implementing the Kalman filter in the localization algorithm helps strengthen the technique and improve the success rate in the presence of measurement malfunctions. A series of trials were carried out to an optimal level utilizing the Taguchi technique to determine the most influential parameter among them. Taguchi's experimental research demonstrated that the number of nodes is the most influential factor in reducing inaccuracy in Wireless Sensor Network (WSN) localization.