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The Study, Based On The Positioning Of Wireless Sensor Networks

Posted on:2011-09-12Degree:MasterType:Thesis
Country:ChinaCandidate:J DingFull Text:PDF
GTID:2208360302998505Subject:Electromagnetic field and microwave technology
Abstract/Summary:PDF Full Text Request
In recent years, with the progress of radio and microelectronics technology, miniature sensor industry has also developed rapidly. Meanwhile, the research about wireless sensor network (WSN) attracts extensive attention. The WSN can be arranged in a broad area and be used to monitor the environmental parameter, for example, pressure, temperature, humidity and so on. But if we don't know the position corresponding to these parameters, it will be meaningless to obtain these parameters. So node positioning technology itself becomes one of the keying technologies of wireless sensor network.In this paper, the author firstly presents the classification and standard for localization algorithms of wireless sensor network technology. Then the existing positioning methods are simply described. After comparing the advantages and disadvantages of several positioning methods, the author study a modified iterative maximum likelihood estimation algorithm and analyzes its advantages and disadvantages, then a hybrid iterative algorithm is proposed, and compares its location algorithm with the traditional one. By comparing with traditional position algorithm, we can find the proposed algorithm can reduce computing time and improve positioning accuracy.In order to solve the problem that insufficient anchor nodes will influence the positioning accuracy, the author uses mobile position algorithm based on virtual anchor nodes. The anchor nodes can greatly be reduced through moving, which can reduce the network and communication cost.Finally, tracking of mobile target that enters into the wireless sensor network is researched in this paper. By researching Kalman filtering method, combing the feature of WSN nodes, the author applies the variable dimension filter with maneuvering target detection ability to the positioning of WSN nodes. The numerical results show that this method is stable and accurate when the target is moving in uniform or variable speed.
Keywords/Search Tags:Wireless Sensor Network, Localization, Filtering target tracking, Iterative Blending Algorithm
PDF Full Text Request
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