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Research On Fusion Base On WiFi Signal Intensity And Inertial Measurement Information Of Indoor Position

Posted on:2016-12-13Degree:MasterType:Thesis
Country:ChinaCandidate:Z M QinFull Text:PDF
GTID:2308330479984866Subject:Computer application technology
Abstract/Summary:PDF Full Text Request
With the development of mobile internet technology and intelligent mobile phone, the people demand more and more services based on indoor location, such as shopping navigation, search car ofgarage, navigation, rescue scene, furnishing location awareness of smart Home. Adaptability to environmental changes and reliability is an important branch attracted more and more attention in indoor position. At the same time, the intelligent equipment handling capability and built-in sensors had increase, it has conditions use intelligent equipment in indoor positioning.A variety of indoor positioning technology has proposed, the indoor positioning technology base on signal strength has advantage of low cost, and not need additional hardware etc. But, it has low positioning precision and poor reliability, poor adaptability to environmental change, which caused by complex indoor environments. Inertial measurement positioning is not affected by the indoor environment, but it exists accumulate error. For the above short comings location access point selection method, similarity weighted fusion algorithm, dynamic loss calculation of distance parameter was proposed, to improve the indoor positioning accuracy and adaptability to environmental change, the research contents of this paper are as follows:1)Positioning signal strength model needs to obtain the indoor signal strength and location information in the pre positioning to calculate positioning model parameter, but when the indoor environment changes, the parameter will be expired, so, it’s poor adaptability to environmental change. In order to improve the positioning method of adaptability to environmental change, our paper proposed method to dynamic calculation parameter, it combine access points signal strength and location of each other, to calculate dynamic model parameters, which improve adaptability to environment and reduce error of location parameter expired.2) Obtain indoor signal strength data under different indoor environment factors in experiment, we know that the indoor obstacles, flow of personnel have great influence on indoor position. Choose different access point will have an impact on the positioning accuracy and reliability, method of location-based access point selection method is proposed based on the signal intensity of AP selection method, it’s using the last location of position coordinates to select AP for localization, the method can decrease the effect of the indoor environment of the positioning error.3)although, inertial measurement is not impacted by complex indoor environmental, but it exist accumulation error and cannot get the starting point location. Signal strength position method exist errors on complex indoor environment, but it can get the starting point location. Combining the advantages of two kinds of indoor positioning technology, similarity weighted fusion algorithm was proposed, the signal similarity as the weighted factor to fusion two kinds of position methods location information to calculate the ultimate position.Finally, building hardware and software environment, to develop android indoor positioning experiment system, method of our paper proposed applied to the positioning system, through the experiment results, we know that the precision and performance of the positioning system in the experimental environment can meet the basic requirements of indoor positioning.
Keywords/Search Tags:Signal intensity, Indoor positioning, Dynamic parameter selection, Inertial positioning, Multi source information fusion
PDF Full Text Request
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