Over the past few decades, leveraging the advancements in Vehicle-to-everything (V2X) technologies, CP techniques have emerged as a promising way to enhance the vehicle positioning performance by fusing positioning-related information from a group of participating vehicles travelling in dense urban environments. Especially, the CP performance could be further improved by introducing SRVs into CP networks, which is called SRV-aided CP. Unfortunately, due to the signal blockage and reflection in urban environments, CP systems may split into several sub-clusters that cannot be connected with each other in dense urban environments, in which the sub-clusters with few SRVs will suffer from degradation of CP performance. However, most of existing networking strategies mainly concentrate on integrating the positioning-related information within a cluster and overlooking some potential inter-cluster information. Thus, there is a clear demand for a more accessible, reliable approach to fully utilize inter-cluster potential information and improve the positioning performance of the whole CP systems.
Recently, a team of researchers led by Hongbo Zhao from Beihang University, China have introduced an Unmanned Aerial Vehicle (UAV) into the SRV-aided CP network and designed a locally-centralized CP method based on clustering optimization strategy for this CP network. This work not only provides a complete solution for inter-node communication, but also fully integrates the positioning resources of the entire network, aiming to improve the CP performance of SRV-aided networks.
The team published their work in the Chinese Journal of Aeronautics on May 28, 2025.
"In this work, we propose the clustering optimization strategy to fully integrate whole-net information and achieve data fusion for the CP system aided by UAV, using double differential Global Navigation Satellite System (GNSS) baseline and inter-node ranging measurements. Firstly, we formulate an inter-cluster communication scheme to achieve the information interaction. The UAV is utilized to communicate with high precision cluster and broadcast information to multiple low precision clusters. Then, we design the clustering optimization strategy, which cooperates high precision nodes with low precision sub-clusters, to achieve whole-net optimization. Finally, we utilize the locally-centralized factor graph optimization algorithm for each optimized cluster to complete data fusion." said Hongbo Zhao, professor at School of Electronics and Information Engineering at Beihang University (China), a senior expert whose research interests include multi-node cooperative positioning and non-terrestrial communication network.
"Compared with the CP strategies that only consider the positioning-related information within a cluster, the strategy we proposed can make full use of inter-cluster potential available CP information and achieve higher CP performance. The simulation results show that the RMSE for the low precision cluster declines from 0.98 m to 0.40 m, and the RMSE for the high precision cluster also declines from 0.65 m to 0.22 m by using our method. These results indicate that the positioning accuracy and reliability of CoVs can be improved by utilizing available potential information from high-precision nodes." said Hongbo Zhao.
Furthermore, Zhao put forward two major development directions may be pursued in future works. Firstly, Zhao intend to evaluate the impact of communication latency and positioning-related resource constraints to design a clustering optimization strategy for large-scale CP networks. Moreover, Zhao will consider to introduce more aerial cooperators into the CP system to further construct an aerial CP network, which can better assist ground nodes in inter-node communication, position awareness and path planning.
Original Source
Hongbo ZHAO, Zeqi YIN, Shan HU. Clustering optimization strategy for cooperative positioning system aided by UAV [J]. Chinese Journal of Aeronautics, 2025, https://doi.org/10.1016/j.cja.2025.103594.
About Chinese Journal of Aeronautics
Chinese Journal of Aeronautics (CJA) is an open access, peer-reviewed international journal covering all aspects of aerospace engineering, monthly published by Elsevier. The Journal reports the scientific and technological achievements and frontiers in aeronautic engineering and astronautic engineering, in both theory and practice. CJA is indexed in SCI (IF = 5.7, Q1), EI, IAA, AJ, CSA, Scopus.
