An improved optimization localization algorithm in WSNs

Node localization of wireless sensor networks (WSNs) is a key problem in the practical applications. To improve the localization accuracy and reduce the cost, an improved localization algorithm based on particle swarm optimization (PSO) is proposed. In the algorithm, the idea of proactive estimate is introduced to estimate the area of nodes, reduce and restrict the solution space, so as to quicken the search speed of particles, and then the idea of competition evolution and adaptive weighting are used to enhance the global and local search ability when accelerating convergence speed. Simulation results show that, compared with other similar methods, the proposed algorithm can make more effective use of anchor node information, reduce the cost of network, and increase positioning accuracy while significantly reducing the calculation amount. Moreover the algorithm shows robust for communication ranging error.