{"title":"多传感器多oosm分布式序列融合滤波","authors":"Feng Xiaoliang, Wen Chenglin, Xu Lizhong","doi":"10.1109/ICCA.2013.6564995","DOIUrl":null,"url":null,"abstract":"Multi-sensor fusion for OOSM system is still an open question in the field of wireless sensor network. In this paper, a new distributed sequential fusion algorithm for multi-sensor system with one-step-lag OOSMs is proposed in the sense of minimum trace of error covariance matrix. The main idea of this real time sequential fusion algorithm is that: firstly, an equivalent measurement “sampled” at the fusion time is obtained, once a measurement comes to the fusion center; then, a local estimation of the current state is obtained based on the equivalent measurement; furthermore, first round fusion is carried out for the second local estimate and the first local estimate to obtain the first local fusion when the second measurement comes; another round of fusion process is carried out for the third local estimate and the first local fusion estimation. Repeating this process until all the measurements are fused, sequentially. The final simulation illustrates its efficiency and validity of the proposed method.","PeriodicalId":336534,"journal":{"name":"2013 10th IEEE International Conference on Control and Automation (ICCA)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Multi-sensor multi-OOSM distributed sequential fusion filtering\",\"authors\":\"Feng Xiaoliang, Wen Chenglin, Xu Lizhong\",\"doi\":\"10.1109/ICCA.2013.6564995\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Multi-sensor fusion for OOSM system is still an open question in the field of wireless sensor network. In this paper, a new distributed sequential fusion algorithm for multi-sensor system with one-step-lag OOSMs is proposed in the sense of minimum trace of error covariance matrix. The main idea of this real time sequential fusion algorithm is that: firstly, an equivalent measurement “sampled” at the fusion time is obtained, once a measurement comes to the fusion center; then, a local estimation of the current state is obtained based on the equivalent measurement; furthermore, first round fusion is carried out for the second local estimate and the first local estimate to obtain the first local fusion when the second measurement comes; another round of fusion process is carried out for the third local estimate and the first local fusion estimation. Repeating this process until all the measurements are fused, sequentially. The final simulation illustrates its efficiency and validity of the proposed method.\",\"PeriodicalId\":336534,\"journal\":{\"name\":\"2013 10th IEEE International Conference on Control and Automation (ICCA)\",\"volume\":\"114 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 10th IEEE International Conference on Control and Automation (ICCA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCA.2013.6564995\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 10th IEEE International Conference on Control and Automation (ICCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCA.2013.6564995","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-sensor fusion for OOSM system is still an open question in the field of wireless sensor network. In this paper, a new distributed sequential fusion algorithm for multi-sensor system with one-step-lag OOSMs is proposed in the sense of minimum trace of error covariance matrix. The main idea of this real time sequential fusion algorithm is that: firstly, an equivalent measurement “sampled” at the fusion time is obtained, once a measurement comes to the fusion center; then, a local estimation of the current state is obtained based on the equivalent measurement; furthermore, first round fusion is carried out for the second local estimate and the first local estimate to obtain the first local fusion when the second measurement comes; another round of fusion process is carried out for the third local estimate and the first local fusion estimation. Repeating this process until all the measurements are fused, sequentially. The final simulation illustrates its efficiency and validity of the proposed method.