Abstract
With the development of smart cities and 5G applications, there is an increasingly urgent need for cooperative positioning among all kinds of intelligent terminals. Existing cooperative positioning technology is primarily designed for two-dimensional positions, and the computing speed and positioning accuracy cannot meet the needs of smart cities. To solve these problems, this paper proposes a factor-graph-aided three-dimensional faster cooperative positioning algorithm (FG-3DCP) that combines a factor graph and sum product theory to establish a cooperative localization model with many nodes. To reduce computational complexity and describe fast positioning, the parameter independence of the factor graph is used, and the positioning data of each node coordinate axis are calculated independently. Then, the positioning result is obtained by fusion, and the computing speed is markedly improved. The proposed algorithm was simulated and analyzed in terms of ranging error, position ambiguity, network topology and the number of nodes. When the proposed algorithm was compared to the existing non-Bayesian estimation cooperative position methods, the position performance improved more than 20%, and the convergence rate was the fastest in the 3D environment.
Highlights
In smart cities, the number of intelligent terminals is growing geometrically, and high-precision cooperative positioning is the core of real-time terminal work
This method uses the idea of highdimensional reconstruction and combines the belief information transfer strategy to obtain an approximate solution of the edge posterior distribution function with the variable nodes on a factor graph
Topology network, ranging error and time synchronization will reduce the performance of the cooperative localization algorithm.A reference node selection method is proposed in [22] and [23], a method to eliminate ranging error is proposed in [24] and cooperative joint localization and clock synchronization based on gaussian message passing is proposed in [25] and [26].These methods solve one problem in the cooperative positioning system, and do not consider the problem of three-dimensional positioning.To solve these problems, this paper proposes a factor-graph-aided three-dimensional fast cooperative positioning algorithm
Summary
The number of intelligent terminals is growing geometrically, and high-precision cooperative positioning is the core of real-time terminal work. An unscented Kalman filter (UKF) cooperative positioning method based on sigma point belief information transfer was proposed in [3] This method uses the idea of highdimensional reconstruction and combines the belief information transfer strategy to obtain an approximate solution of the edge posterior distribution function with the variable nodes on a factor graph. The proposed method uses the knowledge of factor graph theory and the sum product algorithm to construct a belief information [17][18] transfer model for all agents. Based on the calculation criteria of the sum-product algorithm, the paper uses belief information to iterate, transfer and solve in the factor graph, and achieves the positioning of the target node. 2 k (dikq ) m 2xikq m2 zikq , xiq xiq ziq ziq (dk ) m2 m2 diq iq xikq
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