Wireless Node Localization Using Parametric Likelihood Function Based on Distance Ratio Derived from RSSI

In recent years, with the increasing informatization of society, the concept of a super-smart society has been proposed, and technological developments towards its realization are rapidly advancing. The construction of such a society requires a vast amount of information, and technologies such as Wireless Sensor Networks (WSNs) have gained significant attention as effective means of information collection. At this stage, the location information of each node is indispensable for the operation of a WSN; therefore, an appropriate localization system must be designed. The requirements of a localization system include usability in both indoor and outdoor environments, low cost, and low power consumption. Therefore, this aimed to achieve high localization accuracy over a wide area by applying the Apollonius circle locus theory to the received signal strength indicator (RSSI) values from three or more localization reference nodes and by performing maximum likelihood estimation based on a parametric likelihood function. The simulation outcomes demonstrated that the localization error was reduced by approximately 74.8% in a 6m & times;6m area compared to conventional methods, and the 90th-percentile error was suppressed below 0.21m in representative results.