Monte Carlo Localization of Mobile Sensor Networks Using the Position Information of Neighbor Nodes

摘要: Localization is a fundamental problem in wireless sensor networks. Most existing localization algorithm designed for static There are few methods mobile However, Sequential Monte Carlo method (SMC) has been used of networks recently. In this paper, we propose based on SMC which can improve the location accuracy. A new sample generation. that, samples distributes uniformly over area from drawn instead random generation that area. This reduces number required samples; besides, enables to estimate maximum error each node more accurately. Our also uses estimation non-anchor neighbor nodes efficiently than other algorithms. accuracy highly.