Resource Optimization Of Localization Algorithm Based On Non-parametric Belief Propagation

With the development of wireless communication technology,the wireless location technology has aroused the common concern of academia and industry as the base of Internet of Things and other modern industry technology.Because of the low penetrating ability of satellite signals,GPS can not provide location information in complicated environment,which is the most commonly used strategy to provide localization information.Therefore other localization strategies are urgently needed to be supplemented,and wireless cooperative localization network is one of the current mainstream methods.According to the estimation method of localization,the basic algorithm of wireless localization can be divided into non-Bayesian estimation method and Bayesian estimation method.Because the Bayesian estimation makes full use of the priori position information,it is more suitable to be applied to cooperative localization or the location where the target node location has a priori distribution.In this paper,we will explore the advantages and disadvantages of parameter-based belief propagation algorithm and non-parametric belief propagation algorithm and their application limitations in localization.The main contents of this dissertation include the following aspects:Nonparametric belief propagation algorithm is more suitable for real indoor wireless network location because of its low requirement for Gaussian linearity,but it has the disadvantage of large amount of computation and traffic.In this paper,we will optimize nonparametric confidence transfer algorithm for this shortcoming.Based on the existing algorithms,the optimization of computation time and positioning accuracy of positioning algorithm are carried out.The aim of this paper is to reduce the computation time,improve the real-time localization and accuracy of non-parametric belief propagation algorithm under the existing hardware equipment.Optimize resource allocation,and improve resource utilization efficiency.In this paper,we will optimize the allocation of bandwidth resources based on non-parametric belief propagation algorithm.Based on the CRLB theory,the bandwidth of the ranging signal of the target node is optimized for the anchor node.If the anchor node has no value to locate the target node,it does not allocate the bandwidth so as not to allocate the particles for ranging,which can guarantee the full utilization of network resources and communication resources,and improve the positioning accuracy.Aiming at the shortcomings of CRLB theory applied directly to the actual localization algorithm,this paper will propose a low complexity but non-optimal bandwidth allocation strategy based on RII.In this dissertation,the above two aspects of studies will be carried out,then the feasibility of the conclusion is proved by the simulation experiment,which will lay a foundation for the future application of algorithms and contribute to the follow-up research.