A High Precision Localization Method in the Wireless Sensor Network

In a Wireless Sensor Network (WSN), it is necessary to achieve an accurate location of the target node. In classical Biogeography-based Optimization (BBO) algorithm, the initial search range is too large in the process of target node location and the search power is insufficient in the process of convergence. In this case, this paper proposes an improved BBO algorithm based on elite feature variation (EFV-BBO). Additionally, a target node localization method combining EFV-BBO with Weighted Least Square (WLS) algorithm is proposed to achieve high-precision localization. Firstly, the WLS is used to complete the preliminary coarse localization of the target node, and then, the initial search range of EFV-BBO is constrained by WLS estimation. Finally, the EFV-BBO algorithm is used to find the best node location. The improved algorithm WLS-EFV-BBO proposed in this paper enriches the species diversity of offspring and significantly improves the optimization ability of BBO algorithm. Experiments show that the proposed localization method is superior to other algorithms and can achieve high-precision wireless localization, and the average operation time is 0.104s.