Abstract
Aiming at the problem that traditional single ranging method is difficult to ensure the accuracy of wireless sensor networks (WSN) node localization, a least squares support vector regression (LSSVR) node three-dimensional localization algorithm based on received signal strength index (RSSI) and time of arrival (TOA) ranging information is proposed. Firstly, by introducing a single mobile anchor node, three-dimensional localization model of WSN nodes is established based on LSSVR by RSSI and TOA sampling values of virtual nodes. Then, based on the idea of using RSSI ranging in the short distance and TOA ranging in the longer distance, the ranging of nodes in different locations is realized. Finally, the ranging information of RSSI and TOA are used as the input vector of LSSVR localization model to complete the location estimation of unknown nodes. The simulation results of MATLAB show that the proposed algorithm has higher localization accuracy than LSSVR-based or RSSI-TOA-based localization method in the three-dimensional environment with randomly distributed nodes.
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