Abstract:
Aiming at the disadvantage of low positioning accuracy of traditional Monte Carlo Localization method (MCL) algorithm, this paper proposes an improved Monte Carlo Localization algorithm−DEMCL, which is based on distance estimation. First, the estimation distance between the unknown nodes and anchor nodes is calculated based on the network connectivity, anchor node information and adjacent relationship of nodes. Then, a new filter condition is added to the filtering phase of the algorithm to optimize the sample set and reduce positioning errors. And the end of the article, Matlab is used to simulate and analyze the performance of the algorithm. The simulation results show that in the same environment, compared with the MCL algorithm and the MCB algorithm, the DEMCL algorithm can ensure higher positioning accuracy, while reducing the number of invalidly located nodes, the network coverage can reach 98.83%.