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Research Of Wifi Indoor Positioning Technology Based On RSSI Ranging

Posted on:2016-04-02Degree:MasterType:Thesis
Country:ChinaCandidate:J ChenFull Text:PDF
GTID:2308330461959371Subject:Communication and Information System
Abstract/Summary:PDF Full Text Request
With the technology of outdoor positioning mature, people pay attention to the indoor gradually. Indoor positioning technology based on WiFi is attracting attention because of its wide coverage, fast information transmission and low cost. The positioning accuracy is not high because of the complex indoor environment, so the application of precision positioning with the technology of WiFi based on RSSI(Received Signal Strength Indicator) ranging has been limited. For this, I will do the research from three aspects: the processing of RSSI,the estimation of ranging and the localization in this article.In the stage of RSSI pretreatment, the RSSI which fluctuate greatly are singular values, and they will be corrected on the test point. After that, they will be processed again by Gauss filter to reduce their fluctuation range.In the stage of distance estimation, in the view of the three common indoor path attenuation models, the method of EM algorithm is used to estimate a optimal model applicable to the environment of corridor.After that, the parameters in optimal model should be estimated in a real-time method.Therefore, the range can be completed before location.In the positioning stage, a positioning algorithm of adaptive selection combining the method of total least squares and trilateration is proposed to foster strengths and to circumvent weaknesses. Meanwhile, a corrected method of the location result which has a large error is discussed.In the actual environment of corridor, the methods in front research are tested in a system which is a test system of the Wi Fi location and it is achieved by C#. The results proved that the localization algorithm proposed in this article can bring higher accuracy.
Keywords/Search Tags:Wi Fi, RSSI, optimal model, positioning algorithm of adaptive selection, C#
PDF Full Text Request
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