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An Extended Kalman Filter-Based Data Fusion Method for Wireless Sensor Networks

机译:基于扩展卡尔曼滤波器的无线传感器网络数据融合方法

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For the requirement of physiological signal monitoring in the prevention of disease and in early diagnosis, the wireless sensor network plays an important role both for the physiological signal collection and the communication between the user and the remote medical service station. However, most of its energy is wasted during the transmission which shortens the network lifetime. This chapter focuses on the data fusion method with an extended Kalman filter by saving the waste of energy at the source. The expected result is to reduce the waste of energy during the transmission and lengthen the network lifetime. The simulation experiment demonstrates that the proposed method obtains the satisfactory result. It should have a good practical value in the application of physiological signal monitoring embedded in intelligent garment.
机译:对于在疾病预防和早期诊断中需要生理信号监视的需求,无线传感器网络在生理信号收集以及用户与远程医疗服务站之间的通信中都起着重要的作用。但是,其大部分能量在传输过程中被浪费了,从而缩短了网络寿命。本章重点介绍了通过扩展卡尔曼滤波器的数据融合方法,可节省源头的能源浪费。预期结果是减少传输过程中的能量浪费并延长网络寿命。仿真实验表明,该方法取得了满意的结果。在智能服装中嵌入生理信号监测的应用中应具有良好的实用价值。

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