This paper presents a source localization algorithm based on the source signal's time-difference-of-arrival(TDOA) for asynchronous wireless sensor network.To obtain synchronization among anchors,all anchors broadc...This paper presents a source localization algorithm based on the source signal's time-difference-of-arrival(TDOA) for asynchronous wireless sensor network.To obtain synchronization among anchors,all anchors broadcast signals periodically,the clock offsets and skews of anchor pairs can be estimated using broadcasting signal's time-of-arrivals(TOA) at anchors.A kalman filter is adopted to improve the accuracy of clock offsets and track the clock drifts due to random fluctuations.Once the source transmits signal,the TOAs at anchors are stamped respectively and source's TDOA error due to clock offset and skew of anchor pair can be mitigated by a compensation operation.Based on a Gaussian noise model,maximum likelihood estimation(MLE) for the source position is obtained.Performance issues are addressed by evaluating the Cramer-Rao lower bound and the selection of broadcasting period.The proposed algorithm is simple and effective,which has close performance with synchronous TDOA algorithm.展开更多
In recent years,the monitoring systems play significant roles in our life.So,in this paper,we propose an automatic weather monitoring system that allows having dynamic and real-time climate data of a given area.The pr...In recent years,the monitoring systems play significant roles in our life.So,in this paper,we propose an automatic weather monitoring system that allows having dynamic and real-time climate data of a given area.The proposed system is based on the internet of things technology and embedded system.The system also includes electronic devices,sensors,and wireless technology.The main objective of this system is sensing the climate parameters,such as temperature,humidity,and existence of some gases,based on the sensors.The captured values can then be sent to remote applications or databases.Afterwards,the stored data can be visualized in graphics and tables form.展开更多
基金supported by the National Natural Science Foundation of China under Grant No.61571452 and No.61201331
文摘This paper presents a source localization algorithm based on the source signal's time-difference-of-arrival(TDOA) for asynchronous wireless sensor network.To obtain synchronization among anchors,all anchors broadcast signals periodically,the clock offsets and skews of anchor pairs can be estimated using broadcasting signal's time-of-arrivals(TOA) at anchors.A kalman filter is adopted to improve the accuracy of clock offsets and track the clock drifts due to random fluctuations.Once the source transmits signal,the TOAs at anchors are stamped respectively and source's TDOA error due to clock offset and skew of anchor pair can be mitigated by a compensation operation.Based on a Gaussian noise model,maximum likelihood estimation(MLE) for the source position is obtained.Performance issues are addressed by evaluating the Cramer-Rao lower bound and the selection of broadcasting period.The proposed algorithm is simple and effective,which has close performance with synchronous TDOA algorithm.
文摘In recent years,the monitoring systems play significant roles in our life.So,in this paper,we propose an automatic weather monitoring system that allows having dynamic and real-time climate data of a given area.The proposed system is based on the internet of things technology and embedded system.The system also includes electronic devices,sensors,and wireless technology.The main objective of this system is sensing the climate parameters,such as temperature,humidity,and existence of some gases,based on the sensors.The captured values can then be sent to remote applications or databases.Afterwards,the stored data can be visualized in graphics and tables form.
