WSN Localization Method Using Interval Data Clustering

When the wireless sensor network (WSN) range-based localization method is applied to communication dis- tance estimation, RSSI (received signal strength indicator) is assumed linear with the logarithm of corresponding commu- nication distance. But it is always in contradiction with the real communication environment and leads to big localization error. So in this paper, interval data combined with statistic information of RSSI data are used to express the distribution region first, then soft and hard interval data cluster algorithm are used to estimate the communication distance for different uncertainty levels of RSSI data. Next, the RSSI-D estimation results are used in range-based localization methods. Finally, real RSSI data in three typical communication environments are used to evaluate this method. Experiment results show that the proposed localization method using interval data clustering RSSI-D (distance estimation based on RSSI) estimation can get better precision in different environments.