{"title":"多传感器系统协同容错故障检测与噪声方差辨识","authors":"Xin Wang, Shuli Sun, Yingfang Shi","doi":"10.1109/ICEDIF.2015.7280148","DOIUrl":null,"url":null,"abstract":"For the multisensor linear discrete time-invariant stochastic system with unknown noise variances, the new measurement system is constructed by using matrix pseudo-inverse method, which can yield many groups of new measurement sequences by cooperating work. Furthermore, the statistics characteristics of the new measurement sequences are analyzed to determine whether the sensors are faulting or not. The self-tuning cooperation fault-torlerance algorithm are presented. Meanwhile, the linear matrix equations are constructed about measurement noise variances. Then the measurement noise variances are found by solving the equations. A simulation example for a tracking system with 3-sensor shows its effectiveness.","PeriodicalId":355975,"journal":{"name":"2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fault detection and noise variance identifier with cooperation fault-torlerance for multisensor system\",\"authors\":\"Xin Wang, Shuli Sun, Yingfang Shi\",\"doi\":\"10.1109/ICEDIF.2015.7280148\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For the multisensor linear discrete time-invariant stochastic system with unknown noise variances, the new measurement system is constructed by using matrix pseudo-inverse method, which can yield many groups of new measurement sequences by cooperating work. Furthermore, the statistics characteristics of the new measurement sequences are analyzed to determine whether the sensors are faulting or not. The self-tuning cooperation fault-torlerance algorithm are presented. Meanwhile, the linear matrix equations are constructed about measurement noise variances. Then the measurement noise variances are found by solving the equations. A simulation example for a tracking system with 3-sensor shows its effectiveness.\",\"PeriodicalId\":355975,\"journal\":{\"name\":\"2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEDIF.2015.7280148\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEDIF.2015.7280148","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fault detection and noise variance identifier with cooperation fault-torlerance for multisensor system
For the multisensor linear discrete time-invariant stochastic system with unknown noise variances, the new measurement system is constructed by using matrix pseudo-inverse method, which can yield many groups of new measurement sequences by cooperating work. Furthermore, the statistics characteristics of the new measurement sequences are analyzed to determine whether the sensors are faulting or not. The self-tuning cooperation fault-torlerance algorithm are presented. Meanwhile, the linear matrix equations are constructed about measurement noise variances. Then the measurement noise variances are found by solving the equations. A simulation example for a tracking system with 3-sensor shows its effectiveness.