Weighted factor graph aided distributed cooperative position algorithm

With the development of wireless location technology, related services have been popularized in all walks of life, but the traditional localization has poor robustness and low positioning accuracy when the number of anchors is small and the nodes have position ambiguity. In this paper, a distributed cooperative position technique based on weighted factor graph is proposed. Under the premise of fully considering the cooperative nodes ranging error and the coordinated terminal position ambiguity, combining the factor graph and the sum product algorithm, the belief information transfer model is established, and the information from the neighbor nodes is weighted, after the information converges iteratively. The belief information of agents is obtained. The proposed algorithm is compared with the existing LS co-localization algorithm and ML co-localization algorithm in terms of convergence speed, computational complexity and positioning accuracy. The simulation results show that the positioning accuracy of more than 90% agents in the proposed method can reach 3m under the given parameters, and the positioning performance is much better than the other two algorithms.