The first long-term rainfall monitoring experiment using the commercial microwave links(CMLs)network in East China is introduced.The network,located in Jiangyin,Jiangsu Province,consists of 49 links with frequencies r...The first long-term rainfall monitoring experiment using the commercial microwave links(CMLs)network in East China is introduced.The network,located in Jiangyin,Jiangsu Province,consists of 49 links with frequencies ranging from 15 GHz to 26 GHz and lengths from 1.14 km to 4.78 km.An OTT PARSIVEL disdrometer is deployed to refine the local rain-induced attenuation relationship,and the CML observations are compared simultaneously with five rain gauges.The inversion parameters of the CML are optimized by minimizing the error of the accumulated rainfall of historical rainfall events.The inversion results show that the daily accumulated rainfall retrieved by the CMLs agrees well with the rain gauge measurements.As an opportunistic approach to monitor near-surface rainfall with high spatiotemporal representativeness and accuracy,the CML network can be used to monitor and forecast urban flood disasters,especially in regions where the widepread deployment of conventional meteorological instruments is impractical.展开更多
Wireless Sensor Networks for Rainfall Monitoring (RM-WSNs) is a sensor network for the large-scale regional and moving rainfall monitoring,which could be controlled deployment. Delivery delay and cross-cluster calcula...Wireless Sensor Networks for Rainfall Monitoring (RM-WSNs) is a sensor network for the large-scale regional and moving rainfall monitoring,which could be controlled deployment. Delivery delay and cross-cluster calculation leads to information inaccuracy by the existing dynamic collabo-rative self-organization algorithm in WSNs. In this letter,a Local Dynamic Cluster Self-organization algorithm (LDCS) is proposed for the large-scale regional and moving target monitoring in RM-WSNs. The algorithm utilizes the resource-rich node in WSNs as the cluster head,which processes target information obtained by sensor nodes in cluster. The cluster head shifts with the target moving in chance and re-groups a new cluster. The target information acquisition is limited in the dynamic cluster,which can reduce information across-clusters transfer delay and improve the real-time of information acquisition. The simulation results show that,LDCS can not only relieve the problem of "too frequent leader switches" in IDSQ,also make full use of the history monitoring information of target and con-tinuous monitoring of sensor nodes that failed in DCS.展开更多
基金This research was funded by the China Postdoctoral Science Foundation(2021M701650)the Excellent Youth Scholars of the Natural Science Foundation of Hunan Province of China(2021JJ20046)+1 种基金the Open Grants of the State Key Laboratory of Severe Weather(Grant 2021LASW-A01)the National Natural Science Foundation of China(Grant No.42222505).
文摘The first long-term rainfall monitoring experiment using the commercial microwave links(CMLs)network in East China is introduced.The network,located in Jiangyin,Jiangsu Province,consists of 49 links with frequencies ranging from 15 GHz to 26 GHz and lengths from 1.14 km to 4.78 km.An OTT PARSIVEL disdrometer is deployed to refine the local rain-induced attenuation relationship,and the CML observations are compared simultaneously with five rain gauges.The inversion parameters of the CML are optimized by minimizing the error of the accumulated rainfall of historical rainfall events.The inversion results show that the daily accumulated rainfall retrieved by the CMLs agrees well with the rain gauge measurements.As an opportunistic approach to monitor near-surface rainfall with high spatiotemporal representativeness and accuracy,the CML network can be used to monitor and forecast urban flood disasters,especially in regions where the widepread deployment of conventional meteorological instruments is impractical.
基金Supported by the Key Projection of Science and Technology Research of Ministry of Education of China (107057)the Science & Technology Fund for Students of Hohai University (K200803)
文摘Wireless Sensor Networks for Rainfall Monitoring (RM-WSNs) is a sensor network for the large-scale regional and moving rainfall monitoring,which could be controlled deployment. Delivery delay and cross-cluster calculation leads to information inaccuracy by the existing dynamic collabo-rative self-organization algorithm in WSNs. In this letter,a Local Dynamic Cluster Self-organization algorithm (LDCS) is proposed for the large-scale regional and moving target monitoring in RM-WSNs. The algorithm utilizes the resource-rich node in WSNs as the cluster head,which processes target information obtained by sensor nodes in cluster. The cluster head shifts with the target moving in chance and re-groups a new cluster. The target information acquisition is limited in the dynamic cluster,which can reduce information across-clusters transfer delay and improve the real-time of information acquisition. The simulation results show that,LDCS can not only relieve the problem of "too frequent leader switches" in IDSQ,also make full use of the history monitoring information of target and con-tinuous monitoring of sensor nodes that failed in DCS.
