{"title":"基于改进粒子群算法的超宽带室内定位基站定位研究","authors":"Rui Xue, Zedong Liang","doi":"10.1109/EEI59236.2023.10212636","DOIUrl":null,"url":null,"abstract":"In order to explore the influence of Ultra-Wide Band (UWB) base station location on indoor positioning accuracy, a UWB-based three-dimensional spatial positioning model is established, and the UWB base station location is equivalent to the intelligent optimization problem of multiple points. Particle Swarm Optimization (PSO) algorithm is a classical intelligent optimization algorithm, which can be used to solve the UWB base station location problem through function mapping. Aiming at the problem of slow convergence and easy to fall into local optimum in the location process of traditional PSO algorithm, a particle swarm update strategy is introduced into this paper. The strategy introduces an adaptive mutation mechanism in the PSO algorithm, and updates the particle state twice according to the probability principle to improve the traversal and optimization ability of the particle swarm. Theoretical analysis and experimental results show that under the same optimal fitness, the improved PSO compared with PSO algorithm not only converges faster, but also has higher location accuracy; under the same parameters and simulation conditions, the improved PSO compared with PSO algorithm has shorter execution time.","PeriodicalId":363603,"journal":{"name":"2023 5th International Conference on Electronic Engineering and Informatics (EEI)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Ultra -wideband Indoor Positioning Base Station Location Based on Improved Particle Swarm Optimization Algorithm\",\"authors\":\"Rui Xue, Zedong Liang\",\"doi\":\"10.1109/EEI59236.2023.10212636\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to explore the influence of Ultra-Wide Band (UWB) base station location on indoor positioning accuracy, a UWB-based three-dimensional spatial positioning model is established, and the UWB base station location is equivalent to the intelligent optimization problem of multiple points. Particle Swarm Optimization (PSO) algorithm is a classical intelligent optimization algorithm, which can be used to solve the UWB base station location problem through function mapping. Aiming at the problem of slow convergence and easy to fall into local optimum in the location process of traditional PSO algorithm, a particle swarm update strategy is introduced into this paper. The strategy introduces an adaptive mutation mechanism in the PSO algorithm, and updates the particle state twice according to the probability principle to improve the traversal and optimization ability of the particle swarm. Theoretical analysis and experimental results show that under the same optimal fitness, the improved PSO compared with PSO algorithm not only converges faster, but also has higher location accuracy; under the same parameters and simulation conditions, the improved PSO compared with PSO algorithm has shorter execution time.\",\"PeriodicalId\":363603,\"journal\":{\"name\":\"2023 5th International Conference on Electronic Engineering and Informatics (EEI)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 5th International Conference on Electronic Engineering and Informatics (EEI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EEI59236.2023.10212636\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 5th International Conference on Electronic Engineering and Informatics (EEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EEI59236.2023.10212636","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Ultra -wideband Indoor Positioning Base Station Location Based on Improved Particle Swarm Optimization Algorithm
In order to explore the influence of Ultra-Wide Band (UWB) base station location on indoor positioning accuracy, a UWB-based three-dimensional spatial positioning model is established, and the UWB base station location is equivalent to the intelligent optimization problem of multiple points. Particle Swarm Optimization (PSO) algorithm is a classical intelligent optimization algorithm, which can be used to solve the UWB base station location problem through function mapping. Aiming at the problem of slow convergence and easy to fall into local optimum in the location process of traditional PSO algorithm, a particle swarm update strategy is introduced into this paper. The strategy introduces an adaptive mutation mechanism in the PSO algorithm, and updates the particle state twice according to the probability principle to improve the traversal and optimization ability of the particle swarm. Theoretical analysis and experimental results show that under the same optimal fitness, the improved PSO compared with PSO algorithm not only converges faster, but also has higher location accuracy; under the same parameters and simulation conditions, the improved PSO compared with PSO algorithm has shorter execution time.