Fast Localization With Unknown Transmit Power and Path-Loss Exponent in WSNs Based on RSS Measurements

Unlike most studies assuming exact knowledge of the transmit power and path-loss exponent, we address the localization problem under a more practical assumption that the exact values of the transmit power and/or path-loss exponent are unavailable. We propose an algorithm based on the differential evolution, opposition based learning, and adaptive redirection that jointly estimates the position of the target node and the parameters. Results from simulation and indoor experiments show that the proposed algorithm provides higher localization accuracy and requires less computational time than conventional algorithms especially when the exact values of the transmit power and path-loss exponent are unavailable simultaneously.