AP Reduction Algorithm For Wi-Fi Indoor Localization In Unknown Environment

With the development of wireless network technology,localization has become a necessary requirement in people's daily lives.In outdoor environment,the Global Positioning System(GPS)can meet people's requirements.However,in indoor environment,the obstruction of the building makes the indoor GPS signal very weak and cannot be used for localization.In recent years,the fingerprint localization technology using the existing indoor Wi-Fi infrastructure has been focused considering the factors of economy and convenience.Under the circumstance,fingerprint localization is required to conduct in an unknown environment,which brings the following two problems: One is that the Access Point(AP)status is unknown.A mobile AP opened by a mobile device will decrease the location dependence of fingerprint signal composed of Received Signal Strength(RSS),which will affect the localization accuracy.The other is that the number of APs is unknown.Too many Aps in the indoor environment will also bring unnecessary storage and computing overhead to fingerprint localization system.Based on this,the specific work of this thesis is as follows:First of all,a detail theoretical proof has been made about the impact of mobile Aps on localization systems.The Wi-Fi fingerprint localization process is analogized to the information propagation process.The analog channel is simulated as a color Gaussian noise channel.By deriving the capacity of the color Gaussian noise channel,the lower limit of the positioning error is obtained.Under above derivation,the negative impact of the mobile AP on the positioning system is proved.Secondly,in order to solve the problem that the localization accuracy of the system decreases due to unknown AP status,a joint judgment criterion for mobile APs is proposed in this thesis.Considering the actual distribution characteristics of Wi-Fi signals,mobile AP detection sub-criteria are established from two perspectives: signal distribution range and signal distribution dispersion.Next,the advantages of the two sub-criteria are combined and a joint judgment criterion for mobile AP detection is established.After detecting and removing mobile APs to the greatest extent possible,the accuracy of Wi-Fi fingerprint indoor localization is improved.Finally,in order to solve the problem that the unknown number of APs brings unnecessary overhead to the localization system,a redundant AP reduction algorithm based on fuzzy rough sets is proposed.A fuzzy rough decision-making system is established,with RSS signals from each AP as conditional attributes,and the division results of positioning target areas as decision-making attributes.Applying the fuzzy rough set reduction algorithm based on information entropy,the redundant APs are removed to the maximum,which can be replaced by other APs in the environment.After that,the storage and calculation overhead of Wi-Fi fingerprint indoor positioning system is reduced.