{"title":"无线传感器网络中目标定位的信道感知自适应量化","authors":"Guiyun Liu, Hua Liu, Hongbin Chen, Jianhua Xiang, Zhong Xiao","doi":"10.1109/WiSEE.2013.6737549","DOIUrl":null,"url":null,"abstract":"This paper considers the problem of quantization schemes for source localization in wireless sensor networks. First, a channel-aware adaptive quantization scheme for target location estimation is proposed and local sensor nodes dynamically adjust their quantization thresholds according to a kind of position-based information sequences. The scheme incorporates the statistics of imperfect wireless channels between sensors and the fusion center. Furthermore, the appropriate maximum likelihood estimator (MLE) and the performance metric Cramér-Rao lower bound (CRLB) are derived. Simulation results are presented to show that the appropriated CRLB is less than the fixed-quantization channel-aware CRLB and the proposed MLE will approach its CRLB when the number of sensors is large enough.","PeriodicalId":127644,"journal":{"name":"IEEE International Conference on Wireless for Space and Extreme Environments","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Channel aware adaptive quantization for target localization in wireless sensor networks\",\"authors\":\"Guiyun Liu, Hua Liu, Hongbin Chen, Jianhua Xiang, Zhong Xiao\",\"doi\":\"10.1109/WiSEE.2013.6737549\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper considers the problem of quantization schemes for source localization in wireless sensor networks. First, a channel-aware adaptive quantization scheme for target location estimation is proposed and local sensor nodes dynamically adjust their quantization thresholds according to a kind of position-based information sequences. The scheme incorporates the statistics of imperfect wireless channels between sensors and the fusion center. Furthermore, the appropriate maximum likelihood estimator (MLE) and the performance metric Cramér-Rao lower bound (CRLB) are derived. Simulation results are presented to show that the appropriated CRLB is less than the fixed-quantization channel-aware CRLB and the proposed MLE will approach its CRLB when the number of sensors is large enough.\",\"PeriodicalId\":127644,\"journal\":{\"name\":\"IEEE International Conference on Wireless for Space and Extreme Environments\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE International Conference on Wireless for Space and Extreme Environments\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WiSEE.2013.6737549\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on Wireless for Space and Extreme Environments","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WiSEE.2013.6737549","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Channel aware adaptive quantization for target localization in wireless sensor networks
This paper considers the problem of quantization schemes for source localization in wireless sensor networks. First, a channel-aware adaptive quantization scheme for target location estimation is proposed and local sensor nodes dynamically adjust their quantization thresholds according to a kind of position-based information sequences. The scheme incorporates the statistics of imperfect wireless channels between sensors and the fusion center. Furthermore, the appropriate maximum likelihood estimator (MLE) and the performance metric Cramér-Rao lower bound (CRLB) are derived. Simulation results are presented to show that the appropriated CRLB is less than the fixed-quantization channel-aware CRLB and the proposed MLE will approach its CRLB when the number of sensors is large enough.