Research on Target Localization Based on Adaptive Particle Swarm Optimization Algorithm

A new method of target localization based on adaptive particle swarm optimization algorithm is proposed in view of the shortcoming of the existing localization algorithm and standard particle swarm optimizer algorithm, which has a complex calculation and is easy to be trapped in local optimum.The method has improved the inertia weight of the standard particle swarm optimizer algorithm, selected the particle swarm, and added adaptive mutation operation in iteration process to enhance its ability to break away from localoptimum, which the mutation probability is adaptively adjusted by variance of the population's fitness.The simulation results indicate that it could carry on the localization effectively through adopting the adaptive particle swarm optimization algorithm.when the variance of random noise interference is 0.5, the localization RMSE is below 0.8 m.