Research On Self-positioning Prompting WiFi Positioning Algorithm

With the location based service more widely used, the demand for location basedservice becomes increasingly strong. The traditional location-based services such as GPSand other location information is to provide outdoor and indoor environments, especially ina closed environment has mobility, GPS and other positioning means useless. Peopleurgently need a way to determine the indoor location information, wireless positioningmethod aims to provide a good prospect.With the increasing use of WiFi LAN and mobile phone antenna on received signalstrength measurements become more accurate. The wireless positioning method makinguse of received signal strength (RSS) has improve the accuracy. This paper focuses on theRSS-based localization algorithm of WiFi Positioning, and suggests improvements andoptimization. This paper mainly involves the following:Firstly, this paper briefly introduces the characteristics of the wireless communicationsystem and the main points of wireless location technologies, and compares and analysseveral typical existing wireless location technologies, sums up the advantages anddisadvantages of existing positioning technologies.Then, based on two typical RSS positioning methods of analysis and improvement,for the lack of triangulation algorithm the paper designs a gray-Markov localizationalgorithm with the existing location algorithm is different, the method of analyzing a largenumber of RSS data get the right distance factor and dynamic loss factor. This reduces theimpact of the complex environment of the indoor localization algorithm to some extent.Location fingerprinting positioning method for positioning method of updating need toconsume a lot of manpower disadvantage, this paper designs a self-localization algorithmflow tips. The use of short-term forecasts for RSS historical data obtained within a certainerror range of the predicted value. By comparing the predicted and actual values, itsuggests whether AP hotspot position is changed, in order to achieve the self promptsfingerprint localization algorithm reduces AP hotspot location data update human input. Finally, the two methods are field-tested and validated data to obtain the error rangeand compare with the general positioning methods. Test results show that self-positioningtips WiFi positioning algorithm can achieve the purpose of positioning, and can achieve theposition change tips and updates.