Optimization Algorithm of RSSI Transmission Model for Distance Error Correction

Abstract

In wireless sensor networks localization process, RSSI-based ranging methods mostly adopt the traditional logarithmic-distance path loss model. Its model parameters mostly adopt empirical values and ignoring the problem of changes in the surrounding environment during the node localization process. Thus, it is increasing the localization error and reducing the applicability of the algorithm. To solve this problem, this paper proposes an optimization algorithm of RSSI transmission model for distance error correction (RSSI-DEC) to optimize the path loss factor and the reference path loss between anchor nodes in the signal transmission model. FA algorithm and PSO algorithm are used to optimize the parameters of the model, and the model parameters adapted to the monitoring environment are obtained to correct the ranging error. The simulation results show that RSSI-DEC algorithm proposed in this paper can effectively improve node localization accuracy and environmental adaptability. The algorithm proposed in this paper has an average relative localization error of 9.17%.