Research Article
Distributed Cooperative Positioning Algorithm Based on Message Passing Using Box Particles in UAVs Networks
@INPROCEEDINGS{10.1007/978-3-030-69069-4_3, author={Lu Lu and Mingxing Ke and Guangxia Li and Shiwen Tian and Tianwei Liu}, title={Distributed Cooperative Positioning Algorithm Based on Message Passing Using Box Particles in UAVs Networks}, proceedings={Wireless and Satellite Systems. 11th EAI International Conference, WiSATS 2020, Nanjing, China, September 17-18, 2020, Proceedings, Part I}, proceedings_a={WISATS}, year={2021}, month={2}, keywords={UAVs networks Cooperative positioning Factor graph Belief propagation Box particles Interval analysis}, doi={10.1007/978-3-030-69069-4_3} }- Lu Lu
Mingxing Ke
Guangxia Li
Shiwen Tian
Tianwei Liu
Year: 2021
Distributed Cooperative Positioning Algorithm Based on Message Passing Using Box Particles in UAVs Networks
WISATS
Springer
DOI: 10.1007/978-3-030-69069-4_3
Abstract
Distributed cooperative positioning has become more and more attractive for large-scale unmanned aerial vehicles (UAVs) networks. In this paper, inspired by the box particle filter which combines interval analysis and Monte Carlo methods, a novel distributed cooperative positioning algorithm named Box-Particles Message Passing (BPMP) is proposed. In BPMP, the expressions of messages cannot be obtained in a closed form by belief propagation (BP) algorithm due to the nonlinearity of models and the complexity of computation. Accordingly, we use non-parametric belief propagation (NBP) also known as message passing methodology with a set of box particles to solve the inference problem of cooperative positioning on factor graph (FG) model in a 3-dimensional UAVs network. The proposed BPMP algorithm can reduce the number of particles while maintaining high accuracy. Simulation results demonstrate the effectiveness of proposed BPMP algorithm.
