Distribute localization for wireless sensor networks using particle swarm optimization

Abstract

Localization is one the key technologies of wireless sensor networks, and the problem of localization is always formulate as an optimization problem. Particle swarm optimization (PSO) is easy to implement and requires moderate computing resources, which is feasible for localization of sensor network. To improve the efficiency and precision of PSO-based localization methods, this paper proposes a distributed PSO-based method. Based on the probabilistic distribution of ranging error, it presents a new objective function to evaluate the fitness of particles. Moreover, it tries to localize as many unknown nodes as possible in a more accurate search space. Simulation results show that the proposed method outperforms previous proposed algorithms.