{"title":"煤矿井下无线传感器网络的改进加权质心定位算法","authors":"Haibo Liu, Yujie Dong, Fuzhong Wang","doi":"10.1504/ijsn.2020.10028585","DOIUrl":null,"url":null,"abstract":"In view of the practical characteristics of coal mine underground working environment and the low positioning accuracy of existing algorithm, an improved weighted centroid localisation algorithm based on received signal strength indicator (RSSI) is proposed. Firstly, the environmental parameters of RSSI ranging are modified by the least square method to eliminate the influence of various interferences on the measured data. The exponential factor and the modified RSSI value are directly calculated to determine the coordinates of the unknown node. The exponential factor is optimised by an improved quantum particle swarm optimisation algorithm based on the criterion of minimum root mean square error. The simulation results show that the proposed algorithm can reduce the influence of complex environment factors in the positioning process and has the better positioning accuracy than the traditional method, which meets requirements of personnel location precision in underground long-distance roadway.","PeriodicalId":39544,"journal":{"name":"International Journal of Security and Networks","volume":"87 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An improved weighted centroid localisation algorithm for wireless sensor networks in coal mine underground\",\"authors\":\"Haibo Liu, Yujie Dong, Fuzhong Wang\",\"doi\":\"10.1504/ijsn.2020.10028585\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In view of the practical characteristics of coal mine underground working environment and the low positioning accuracy of existing algorithm, an improved weighted centroid localisation algorithm based on received signal strength indicator (RSSI) is proposed. Firstly, the environmental parameters of RSSI ranging are modified by the least square method to eliminate the influence of various interferences on the measured data. The exponential factor and the modified RSSI value are directly calculated to determine the coordinates of the unknown node. The exponential factor is optimised by an improved quantum particle swarm optimisation algorithm based on the criterion of minimum root mean square error. The simulation results show that the proposed algorithm can reduce the influence of complex environment factors in the positioning process and has the better positioning accuracy than the traditional method, which meets requirements of personnel location precision in underground long-distance roadway.\",\"PeriodicalId\":39544,\"journal\":{\"name\":\"International Journal of Security and Networks\",\"volume\":\"87 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-04-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Security and Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijsn.2020.10028585\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Security and Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijsn.2020.10028585","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
An improved weighted centroid localisation algorithm for wireless sensor networks in coal mine underground
In view of the practical characteristics of coal mine underground working environment and the low positioning accuracy of existing algorithm, an improved weighted centroid localisation algorithm based on received signal strength indicator (RSSI) is proposed. Firstly, the environmental parameters of RSSI ranging are modified by the least square method to eliminate the influence of various interferences on the measured data. The exponential factor and the modified RSSI value are directly calculated to determine the coordinates of the unknown node. The exponential factor is optimised by an improved quantum particle swarm optimisation algorithm based on the criterion of minimum root mean square error. The simulation results show that the proposed algorithm can reduce the influence of complex environment factors in the positioning process and has the better positioning accuracy than the traditional method, which meets requirements of personnel location precision in underground long-distance roadway.