A Cluster-Based Cooperative Localization Algorithm

Abstract

Cooperative localization (CL) is an efficient way to enhance the position estimate by cooperating among agents, especially under an insufficient signal source situation. To realize CL, a suitable network architecture has to be designed. For the centralized CL, all the information is transmitted to a data center to find a global optimal solution for all the agents. Note that the centralized network is not scalable in communication aspect since all the information has to be collected before estimation, which requires complex scheduling for range measurement and measurement report. On the other hand, an agent estimates its own position and exchanges with other agents locally to solve the scalability issue in the distributed CL. However, measurement information collected locally in the distributed scheme is less than measurement information in the centralized scheme, which might degrade the position estimate and cause divergence by propagating position estimate iteratively. In order to solve the scalability issue of centralized CL and the divergence issue of distributed CL, cluster network is adopted in the paper. After cluster formation, an agent estimates its initial position based on intra-cluster measurement in a cluster to obtain a reliable initial position. To further cooperate with the agent of other clusters, the cluster gateway iteratively refines its position estimate with other cluster gateways based on inter- cluster measurement. Simulation results validate that the proposed cluster-based CL outperforms distributed CL.