Research On Indoor Location Technology Based On WiFi

It is not suitable for the use of traditional cellular networks,GPS and other technologies to locate the position in the indoor environment because of the impact of non-line of sight,multipath and other factors.However,WiFi signal is less affected by non-line-of-sight,WiFi hotspot is commonly deployed,the cost to deploy WiFi hotspot is very low,and the coverage of WiFi signal is wide in the indoor environment,so WiFi signal is widely used in indoor positioning.With the increase in demand for location-based services in the indoor environment,the demand for high-precision positioning technology is correspondingly increased.The need for positioning accuracy has led to the research of positioning algorithms.Wireless signal strength can be used to characterize the position information.With the accuracy of the wireless signal strength's measurement,the method based on the strength of the wireless signal is more accuracy.Many excellent scholars at home and abroad study the indoor positioning technology in deeply,and put forward a lot of new positioning ideas,which broadens the research of indoor positioning technology.The focus of this thesis is the localization algorithm which is based on the RSS,and mainly introduces the triangulation algorithm based on RSS and the algorithm based on fingerprint database,and puts forward the optimization and improvement.In this thesis,the advantages and disadvantages of various algorithms which are ranging and without ranging are deeply understood.In the various algorithms,the algorithms suitable for indoor scene mainly are the triangulation algorithm based on RSS ranging and the localization algorithm based on fingerprint database,and the thesis illustrates the need to study these two algorithms.This thesis mainly analyzes and improves the triangular positioning algorithm based on RSS ranging and the algorithm based on fingerprint database.In view of the shortcomings of weight assignment and RSS data processing in triangulation algorithm,PE weighted triangular centroid localization algorithm is proposed.Different from the existing algorithm,this method first filters out a large collected number of RSS data,and then proposes a new weight calculation method to improve the accuracy of positioning.A new algorithm for fingerprint database localization called NNIA,which is based on the neural network and the traditional fingerprint localization algorithm KNN is proposed,it's used to solve the problem that the effect of reference point distribution and the change of wirelessaccess point.As a result,the method improve the positioning performance.Finally,in the actual indoor scene,RSS data is measured,the above two improved algorithms are applied for simulation test.Comparing with the result of the typical localization algorithm,it can be seen from the comparison result that two different algorithms can improve the accuracy of localization and solve the shortcomings caused by the traditional positioning algorithm,and also it has the advantages which the traditional algorithms do not have.