A Multisensor Fusion-Based Cooperative Localization Scheme in Vehicle Networks

Abstract

Utilizing the measured distance and information exchanged between two different nodes to cooperatively locate in a mobile network has become a solution to replace global navigation satellite system (GNSS) positioning. However, the localization accuracy of the belief propagation-based cooperative localization scheme is substantially influenced by the number of neighbors. In this paper, we propose a cooperative localization scheme combined with a trajectory tracking algorithm. With an insufficient number of neighbors, the trajectory tracking algorithm is utilized to participate in the positioning process of agents. Concretely, we carry out sensor information fusion and utilize quantum-behaved, particle-swarm-optimized, bidirectional long short-term memory (QPSO– BiLSTM) as a trajectory tracking strategy, to precisely predict the positions of agents. It is evident from simulations and results that the proposed cooperative localization scheme performs better than the belief propagation (BP)-based cooperative localization scheme in position error.