An Improved PSO Algorithm for Distributed Localization in Wireless Sensor Networks

• Main Authors: Dan Li, Xian bin Wen
• Format: Article
• Language: English
• Published: SAGE Publishing 2015-07-01
• Series: International Journal of Distributed Sensor Networks
• Online Access: https://doi.org/10.1155/2015/970272

Accurate and quick localization of randomly deployed nodes is required by many applications in wireless sensor networks and always formulated as a multidimensional optimization problem. Particle swarm optimization (PSO) is feasible for the localization problem because of its quick convergence and moderate demand for computing resources. This paper proposes a distributed two-phase PSO algorithm to solve the flip ambiguity problem, and improve the efficiency and precision. In this work, the initial search space is defined by bounding box method and a refinement phase is put forward to correct the error due to flip ambiguity. Moreover, the unknown nodes which only have two references or three near-collinear references are tried to be localized in our research. Simulation results indicate that the proposed distributed localization algorithm is superior to the previous algorithms.