Advanced Combination Localization Algorithm Based on Trilateration for Dynamic Cluster Network

Abstract

Dynamic cluster network localization requires taking the following factors into consideration: 1) the localization time of network nodes; 2) the communication load among all cluster nodes, and; 3) the presence of the abnormal distance measurement data. However, most of the existing network localization algorithms only focus on localization accuracy. To solve the localization problem of the dynamic cluster network nodes, an improved combined trilateral localization algorithm is proposed. This proposed algorithm not only inherits the advantages of trilateration but also addresses the error propagation and accumulation problem with the strategies of anchor nodes selection in combined trilateral localization. Furthermore, by filtering the candidate positions, this algorithm can deal with some abnormal distance measurement data existing in the localization process. Finally, the extensive simulation of the algorithm is performed considering the actual unmanned aerial vehicle (UAV) cluster network, and the experimental results demonstrate the proposed algorithm can achieve high localization accuracy and have robustness as well as good adaptability to the dynamic network.