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《Science of Surveying and Mapping》 2015-06
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Indoor real-time positioning based on Android platform

YANG Kai;GUO Ying;BI Jing-xue;Shandong University of Science and Technology;  
Aiming at the problem of low accuracy of indoor real-time positioning using WiFi signal,this paper presented an improved KNN algorithm.The signal interference caused by humans' walking could make indoor real-time positioning accuracy uncertain.To avoid the error caused by interference in real-time,the improved KNN algorithm monitored the change of WiFi signal strength around the nodes by increasing some external nodes.The signal strength was used to compare with the strength in the fingerprinter database,and the difference could be used to correct the client's positioning results.According to experiments based on Android platform,this algorithm was simple,besides,it could more obviously improve the client's positioning accuracy within the scope of 2.4mfrom the node and the average precision was improved by 0.8m-1mor so.
【CateGory Index】: TN92
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