TY - GEN
T1 - Factor graph aided distributed multi-navigation cooperative positioning algorithm
AU - Tang, Chengkai
AU - Zhang, Lingling
AU - Zhang, Yi
AU - Wang, Ye
N1 - Publisher Copyright:
© 2018 Institute of Navigation. All rights reserved.
PY - 2018
Y1 - 2018
N2 - The development of smart city urgently needs the enhanced accuracy of navigation and positioning service, but the existing navigation technology is difficult to provide further improvement of positioning accuracy. The distributed cooperative positioning technology could increase the navigation and positioning accuracy, but the ranging/positioning error from any cooperative node will lose the effect. This paper presents a distributed cooperative positioning algorithm with factor graph-assisted. It constructs the belief information model by ranging error and positioning error of cooperative nodes, then fuse the positioning information through the factor graph theory. The cooperative nodes can access or disconnect the cooperative network at any time, which effectively avoids the influence of the positioning/ranging error of the cooperative node. The algorithm proposed in this paper is compared to several existing methods from four aspects: ranging error, positioning error of cooperative nodes, convergence speed and mutation error. The simulation results show that the proposed algorithm has 30% - 60% improvement in positioning accuracy compared to other methods under the same ranging error and positioning error. The convergence rate and mutation error elimination times are only one-third to one-fifth of the other methods.
AB - The development of smart city urgently needs the enhanced accuracy of navigation and positioning service, but the existing navigation technology is difficult to provide further improvement of positioning accuracy. The distributed cooperative positioning technology could increase the navigation and positioning accuracy, but the ranging/positioning error from any cooperative node will lose the effect. This paper presents a distributed cooperative positioning algorithm with factor graph-assisted. It constructs the belief information model by ranging error and positioning error of cooperative nodes, then fuse the positioning information through the factor graph theory. The cooperative nodes can access or disconnect the cooperative network at any time, which effectively avoids the influence of the positioning/ranging error of the cooperative node. The algorithm proposed in this paper is compared to several existing methods from four aspects: ranging error, positioning error of cooperative nodes, convergence speed and mutation error. The simulation results show that the proposed algorithm has 30% - 60% improvement in positioning accuracy compared to other methods under the same ranging error and positioning error. The convergence rate and mutation error elimination times are only one-third to one-fifth of the other methods.
UR - http://www.scopus.com/inward/record.url?scp=85062940269&partnerID=8YFLogxK
U2 - 10.33012/2018.15957
DO - 10.33012/2018.15957
M3 - 会议稿件
AN - SCOPUS:85062940269
T3 - Proceedings of the 31st International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2018
SP - 2421
EP - 2428
BT - Proceedings of the 31st International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2018
PB - Institute of Navigation
T2 - 31st International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2018
Y2 - 24 September 2018 through 28 September 2018
ER -