Meanwhile, the optimization methods are both distributed algorithms, so lower energy consumption of position system.The paper fulfills the following work:First, we propose Particle Swarm Optimization (PSO) algorithm to estimate nodes locations, which uses the principle of evolvement and global searching characteristic to find nodes locations. Compared to maximum likelihood estimation method, the simulation results show that PSO method improves the localization accuracy obviously under different ranging errors, as the same time, causing no more communication cost.Second, we propose other localizations system based on GPSO algorithm, which incorporates the advantages of the excellent global searching of the PSO and the local speedy convergence of the gradient method. Experimental simulations show that this proposed method plays better performance than PSO as ranging error increasing, in location precision, convergence speed and robust performance.
